Partial List of Publications (by both graduates and undergraduates)
Morden Deep Learning (New Archtecture, Pretraining, Post-training, Prompt etc.):
Students (alumni): Hao Xiong, Huaijin Wu, Yebin Yang, Zhanpeng Zhou, Yitin Chen, Zhuo Xia, et al.
Q. Liu, X. Zheng, X. Lu, Q. Cao,
Junchi Yan (correspondence)
Rethinking and improving autoformalization: towards a faithful metric and a dependency retrieval-based approach.
International Conference on Learning Representations (ICLR), 2025 spotlight
H. Xiong, Y. Yang (本科生), H. Wu, X. Zhong (本科生), Y. Tang, Z. Xia, X. Wang,
Junchi Yan (correspondence)
In-place Transparent High-order Product for Transformers.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2025.
Y. Li, J. Ma, Y. Yang, Q. Wu, H. Zha,
Junchi Yan (correspondence)
Predictive Consistency Learning with Gradual Label Modeling.
International Conference on Machine Learning (ICML), 2025.
J. Wang, M. Wang, Z. Zhou,
Junchi Yan, W. E, L. Wu
The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training.
International Conference on Machine Learning (ICML), 2025.
A. Han, W. Huang, Z. Zhou, G. Niu, W. Chen,
Junchi Yan, A. Takeda, T. Suzuki
On the Role of Label Noise in the Feature Learning Process.
International Conference on Machine Learning (ICML), 2025.
Z. Zhou, Y. Yong, X. Yang, Junchi Yan (correspondence), W. Hu
Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity.
Neural Information Processing Systems (NeurIPS), 2023
Z. Zhou, M. Wang, Y. Mao, B. Li,
Junchi Yan (correspondence)
Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late In Training .
International Conference on Learning Representations (ICLR), 2025 spotlight
Y. Chen, Junchi Yan (correspondence)
What Rotary Position Embedding Can Tell Us: Identifying Query and Key Weights Corresponding to Basic Syntactic or High-level Semantic Information
Neural Information Processing Systems (NeurIPS), 2024
Y. Chen, J. Bu (本科生), Junchi Yan (correspondence)
Unveiling The Matthew Effect Across Channels: Assessing Layer Width Sufficiency via Weight Norm Variance
Neural Information Processing Systems (NeurIPS), 2024
Z. Zhou, Z. Chen, Y. Chen, B. Zhang,
Junchi Yan (correspondence)
Cross-Task Linearity Emerges in the Pretraining-Finetuning Paradigm.
International Conference on Machine Learning (ICML), 2024.
H. Zhao, X. Yang. Junchi Yan, C. Deng
Dynamic Cognition-aware Spiking Graph Neural Network
AAAI Conference on Artificial Intelligence (AAAI), 2024.
D. Lao, Q. Liu (本科生). J. Bu (本科生). Junchi Yan (correspondence) W. Shen
ViTree: Single-path Neural Tree for Step-wise Interpretable Fine-grained Visual Categorization
AAAI Conference on Artificial Intelligence (AAAI), 2024.
Autonomous Driving and Robotics:
Students (alumni): Xiaosong Jia, Zhenjie Yang, Penghao Wu, Shengchao Hu, Xiaolei Chen, Zhe Ren et al.
李弘扬,
严骏驰, 等
自动驾驶开源数据体系:现状与未来.
中国科学: 信息科学 (SSI), 2024年 [pdf], 2024
廖文龙, 赵华卿,
严骏驰 (通讯作者)
开放道路中匹配高精度地图的在线相机外参标定.
中国图象图形学报 (JIG), 2021
廖宁, 曹敏,
严骏驰 (通讯作者)
视觉提示学习综述.
计算机学报 (CJC), 2024
S. Cai, X. Du
Junchi Yan, S. Shen
Fast and Interpretable 2D Homography Decomposition: Similarity-Kernel-Similarity and Affine-Core-Affine Transformations.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2025
H. Su, F. Song, C. Ma, W. Wu,
Junchi Yan (correspondence)
RoboSense: Large-scale Dataset and Benchmark for Egocentric Robot Perception and Navigation in Crowded and Unstructured Environments.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
Y. Zhu, X. Jia, X. Yang,
Junchi Yan (correspondence).
FlatFusion: Delving into Details of Sparse Transformer-based Camera-LiDAR Fusion for Autonomous Driving
.
International Conference on Robotics and Automation (ICRA), 2025.
Y. Wang, Y. Zhang, X. Hu, L. Niu, J. Zhang, Y. Makihara, Y. Yagi, P. Peng, W. Liao, T. He,
Junchi Yan, L. Zhang.
Pedestrian Motion Reconstruction: A Large-scale Benchmark via Mixed Reality Rendering with Multiple Perspectives and Modalities
.
International Conference on Learning Representations (ICLR), 2025.
K. Yang, Z. Guo, G. Lin, H. Dong, Z. Huang, Y. Wu, D. Zuo, J. Peng, Z. Zhong, X. Wang, Q. Guo, X. Jia,
Junchi Yan, D. Lin.
Trajectory-LLM: A Language-based Data Generator for Trajectory Prediction in Autonomous Driving
.
International Conference on Learning Representations (ICLR), 2025.
X. Jia, J. You, Z. Zhang,
Junchi Yan (correspondence).
DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving
.
International Conference on Learning Representations (ICLR), 2025.
Q. Li, X. Jia, S. Wang,
Junchi Yan (correspondence).
Think2Drive: Efficient Reinforcement Learning by Thinking in Latent World Model for Quasi-Realistic Autonomous Driving (in CARLA-v2).
European Conference on Computer Vision (ECCV), 2024.
Junchi Yan.
Improving Mobile Robot Localization: Grid-based Approach.
Optical Engineering (OE), 2012, 51(2), 024401.
B. Zhang, X. Cai, J. Yuan, D. Yang, J. Guo, X. Yan, R. Xia, B. Shi, M. Dou, T. Chen, S. Liu,
Junchi Yan (correspondence), Y. Qiao.
ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation
.
International Conference on Learning Representations (ICLR), 2024.
X. Zhang (本科生), S. Zhang, Junchi Yan (correspondence)
PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders
Neural Information Processing Systems (NeurIPS), 2024 spotlight
T. Li, P. Jia, B. Wang, C. Li, K. Jiang,
Junchi Yan, H. Li.
LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving.
International Conference on Learning Representations (ICLR), 2024.
R. Zhang, X. Du
Junchi Yan (correspondence), S. Zhang
The Decoupling Concept Bottleneck Model.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2025, 47(2): 1250-1265
X. Jia, P. Wu, L. Chen, H. Li, Y. Liu,
Junchi Yan (correspondence)
HDGT: Heterogeneous Driving Graph Transformer for Multi-Agent Trajectory Prediction via Scene Encoding.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023, 34(2): 573-586
Q. Bu, J. Zeng, L. Chen, Y. Yang, G. Zhou, Junchi Yan, P. Luo, H. Cui, Y. Ma, H. Li
Closed-Loop Visuomotor Control with Generative Expectation for Robotic Manipulation
Neural Information Processing Systems (NeurIPS), 2024
X. Jia, Z. Yang, Q. Li, Z. Zhang,
Junchi Yan (correspondence)
Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving .
Neural Information Processing Systems (NeurIPS), 2024 benchmark track
W. Lia, H. Ma,
Junchi Yan, P. Peng
CalibRBEV: Multi-Camera Calibration via ReversedBird's-eye-view Representations for Autonomous Driving.
ACM Multimedia (MM), 2024
H. Wang, T. Li, Y. Li, L. Chen, C. Sima, Z. Liu, B. Wang, P. Jia, Y. Wang, S. Jiang, F. Wen, H. Xu, P, Luo,
Junchi Yan, W. Zhang, H. Li
OpenLane-V2: A Topology Reasoning Benchmark for Scene Understanding in Autonomous Driving.
Neural Information Processing Systems (NeurIPS), 2023
X. Jia, Y. Gao, L. Chen,
Junchi Yan (correspondence), L. Liu, H. Li
DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving.
IEEE/CVF International Conference on Computer Vision (ICCV) oral, 2023.
X. Hu, Y. Liu, B. Tang,
Junchi Yan, L. Chen
Learning Dynamic Graph for Overtaking Strategy in Autonomous Driving.
IEEE Transactions on Intelligent Transportation Systems (TITS), 2023
X. Jia, P. Wu, L. Chen, J. Xie, C. He,
Junchi Yan (correspondence), H. Li
Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
J. Zeng, L. Chen, H. Deng, L. Lu,
Junchi Yan, Y. Qiao, H. Li
Distilling Focal Knowledge from Imperfect Expert.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
X. Chen, W. Liao, B. Liu,
Junchi Yan (correspondence), T. He,
OpenDenseLane: a New LiDAR-based dataset for HD map construction.
IEEE International Conference on Multimedia and Expo (ICME), 2022.
W. Liao, X. Chen, W. Zhang, H. Liu,
Junchi Yan (correspondence), Y. Lou, T. Xue, S. Mei
Trajectory Prediction from Ego View: a Coordinate Transform and Tail-light Event Driven Approach.
IEEE International Conference on Multimedia and Expo (ICME), 2022.
S. Hu (本科生), L. Chen, P. Wu, H. Li,
Junchi Yan, D. Tao.
ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning
.
European Conference on Computer Vision (ECCV), 2022.
P. Wu (本科生), L. Chen, H. Li, X. Jia,
Junchi Yan, Y. Qiao.
Policy Pre-training for Autonomous Driving via Self-supervised Geometric Modeling
.
International Conference on Learning Representations (ICLR), 2023.
L. Chen, C. Sima, Y. Li, Z. Zheng, J. Xu, X. Geng, H. Li, C. He, J. Shi, Y. Qiao,
Junchi Yan
PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmark.
European Conference on Computer Vision (ECCV), 2022.
X. Jia, L. Chen, P. Wu, J. Zeng,
Junchi Yan (correspondence), H. Li, Y. Qiao
Towards Capturing the Temporal Dynamics for Trajectory Prediction: a Coarse-to-Fine Approach .
Conference on Robotic Learning (CoRL), 2022
P. Wu (本科生), X. Jia, L. Chen,
Junchi Yan (correspondence), H. Li, Y. Qiao
Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline .
Neural Information Processing Systems (NeurIPS), 2022
Q. Zhang (本科生), Y. Li, Y. Luo, W. Shou, M. Foshey,
Junchi Yan, J. Tenenbaum, W. Matusik, A. Torralba
Dynamic Modeling of Hand-Object Interactions via Tactile Sensing.
International Conference on Intelligent Robots and Systems (IROS), 2021
W. Lin, Y. Zhou, H. Xu,
Junchi Yan, M. Xu, J. Wu, Z. Liu.
A Tube-and-Droplet-based Approach for Representing and Analyzing Motion Trajectories.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017, 39(8): 1489-1503
C. Yang, X. Yin, W. Pei, S. Tian, C. Yang, Z. Zuo, C. Zhu,
Junchi Yan.
Tracking Based Multi-Orientation Scene Text Detection: A Unified Framework With Dynamic Programming.
IEEE Transactions on Image Processing (TIP), 2017, 26(7): 3235-3248
Z. Gao,
Junchi Yan , G. Zhai, J. Zhang, Y. Yang, X. Yang.
Learning Local Neighboring Structure for Robust 3D Shape Representation.
AAAI Conference on Artificial Intelligence (AAAI), 2021.
Z. Gao,
Junchi Yan (correspondence), G. Zhai, X. Yang.
Learning Spectral Dictionary for Local Representation of Mesh.
International Joint Conferences on Artificial Intelligence (IJCAI), 2021.
L. Liu, Y. Chen,
Junchi Yan (correspondence), Y. Zheng,
Optimal LED Spectral Multiplexing for NIR2RGB Translation.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
Z. Gao,
Junchi Yan (correspondence), G. Zhai, X. Yang.
Robust Mesh Representation Learning via Efficient Local Structure-aware Anisotropic Convolution.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 34(11), 8566-8578, 2023.
Z. Ren,
Junchi Yan (correspondence), B. Ni, B. Liu, H. Zha, X. Yang.
Unsupervised Deep Learning for Optical Flow Estimation.
AAAI Conference on Artificial Intelligence (AAAI), 2017.
Z. Ren, W. Luo,
Junchi Yan (correspondence), W. Liao, X. Yang, A. Yuille, H. Zha.
STFlow: Self-Taught Optical Flow Estimation Using Pseudo Labels.
IEEE Transactions on Image Processing (TIP), 2020, 29: 9113-9124
Z. Ren,
Junchi Yan (correspondence), X. Yang, A. Yuille, H. Zha.
Unsupervised Learning of Optical Flow With Patch Consistency and Occlusion Estimation.
Pattern Recognition (PR), 2020, Volume 103, 107191
B. Sun,
Junchi Yan, Y. Zheng, X. Zhou.
Tuning IR-cut Filter for Illumination-aware Spectral Reconstruction from RGB.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (oral), 2021.
N. Zhang,
Junchi Yan (correspondence).
Rethinking the Defocus Blur Detection Problem and A Real-Time Deep DBD Model.
European Conference on Computer Vision (ECCV), 2020.
Machine Learning for Graph and Combinatorial Optimization:
Students (alumni): Runzhong Wang, Chang Liu, Yang Li, Haoyu Geng, Han Lu, Yixuan He (Oxford), et al.
汪润中, 郦洋,
严骏驰 (通讯作者), 杨小康
正线性约束组合优化问题的非自回归学习求解.
中国科学: 信息科学 (SSI), 2024年 [pdf], 2024
吴怀瑾, 卜家梓 (本科生), 杨念祖, 孙垚,
严骏驰 (通讯作者)
基于多层次结构建模的药物相互作用类型预测.
中国科学: 信息科学 (SSI), 2025年 [pdf], 2024
J. Ma (本科生), W. Pan, Y. Li,
Junchi Yan (correspondence)
COExpander: Adaptive Solution Expansion for Combinatorial Optimization.
International Conference on Machine Learning (ICML), 2025.
A. Lu,
Junchi Yan (correspondence)
Learning Initial Basis Selection for Linear Programming via Duality-Inspired Tripartite Graph Representation and Comprehensive Supervision.
International Conference on Machine Learning (ICML), 2025.
W. Pan (本科生), H. Xiong, J. Ma (本科生), W. Zhao, Y. Li,
Junchi Yan (correspondence)
UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP
International Conference on Learning Representations (ICLR), 2025.
Y. Li, J. Ma (本科生), W. Pan (本科生), R. Wang, H. Geng, N. Yang,
Junchi Yan (correspondence)
Unify ML4TSP: Drawing Methodological Principles for TSP and Beyond from Streamlined Design Space of Learning and Search
International Conference on Learning Representations (ICLR), 2025.
H. Yuan, W. Ouyang, C. Zhang, Y. Sun, L. Gong,
Junchi Yan.
BTBS-LNS: Binarized-Tightening, Branch and Search on Learning LNS Policies for MIP
International Conference on Learning Representations (ICLR), 2025.
Y. Li, J. Guo (本科生), R. Wang, H. Zha,
Junchi Yan (correspondence)
Fast T2T: Optimization Consistency Speeds up Diffusion-based Training to Testing for Combinatorial Optimization
Neural Information Processing Systems (NeurIPS), 2024
R. Wang, Z. Guo, W. Pan (本科生), Y. Zhang (本科生), J. Ma (本科生), N. Yang (本科生), Q. Liu (本科生), L. Wei (本科生), H. Zhang (本科生), C. Liu, Z. Jiang, X. Yang,
Junchi Yan (correspondence)
Pygmtools: A Python Graph Matching Toolkit.
Journal of Machine Learning Research (JMLR) 25(33):1−7, 2024 Jittor Supported
J. Zhang, C. Liu, X. Li, HL. Zhen, M. Yuan, Y. Li, Junchi Yan (correspondence)
A Survey for Solving Mixed Integer Programming via Machine Learning.
Neurocomputing (NC) 519 (28), 205-217, 2023
W. Guo, H. Zhen, X. Li, W. Luo, M. Yuan, Y. Jin,
Junchi Yan (correspondence)
Machine learning methods in solving the boolean satisfiability problem.
Machine Intelligence Research (MIR) 2023, 20: 640–655
J. Ma, X. Jiang, A. Fan, J. Jiang,
Junchi Yan (correspondence)
Image Matching from Handcrafted to Deep Features: A Survey.
International Journal of Computer Vision (IJCV) 129, 23–79, 2021
J. Yuan, J. Zhang, Z. Cai,
Junchi Yan (correspondence)
Towards Variance Reduction for Reinforcement Learning of Industrial Decision-making Tasks: A Bi-Critic based Demand-Constraint Decoupling Approach.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2023.
H. Geng, R. Wang, F. Wu,
Junchi Yan (correspondence)
GAL-VNE: Solving the VNE Problem with Global Reinforcement Learning and Local One-Shot Neural Prediction.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2023.
R. Wang,
Junchi Yan (correspondence), X. Yang
Combinatorial Learning of Robust Deep Graph Matching: an Embedding based Approach.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2023, 45(6): 6984-7000
[project page]
R. Wang,
Junchi Yan (correspondence), X. Yang
Unsupervised Learning of Graph Matching with Mixture of Modes via Discrepancy Minimization.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2023, 45(8): 10500-10518 [project page]
X. Liu, J. Yang,
Junchi Yan
NCMNet: Neighbor Consistency Mining Network for Two-View Correspondence Pruning.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2024, 46(12): 11254-11272 [project page]
H. Geng, H. Ruan (本科生), R. Wang, Y. Li, Y. Wang, L. Chen, Junchi Yan (correspondence),
Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime.
Neural Information Processing Systems (NeurIPS), 2024 benchmark track
Z. Guo, Y. Li, C. Liu, W. Ouyang,
Junchi Yan (correspondence)
ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation
International Conference on Machine Learning (ICML) spotlight, 2024
Y. Zhang, C. Fan, D. Chen, C. Li, W. Ouyang, M. Zhu,
Junchi Yan
MILP-FBGen: LP/MILP Instance Generation with Feasibility/Boundedness
International Conference on Machine Learning (ICML), 2024
C. Liu, Z. Dong, H. Ma, W. Luo, B. Pang, X. Li, J. Zeng,
Junchi Yan (correspondence)
L2P-MIP: Learning to Presolve for Mixed Integer Programming.
International Conference on Learning Representations (ICLR), 2024.
Z. Jiang, J. Lu, H. Fan (本科生), T. Wang,
Junchi Yan (correspondence).
Learning Structured Universe Graph with Outlier OOD Detection for Partial Matching.
International Conference on Learning Representations (ICLR), 2025.
J. Lu, Z. Jiang, T. Wang,
Junchi Yan (correspondence).
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering.
International Conference on Learning Representations (ICLR), 2024.
C. Zhang, W. Ouyang, H. Yuan, L. Gong, Y. Sun, Z. Guo, Z. Dong,
Junchi Yan
Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach.
International Conference on Learning Representations (ICLR), 2024.
Y. Li, J. Guo (本科生), R. Wang, Junchi Yan (correspondence),
T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization.
Neural Information Processing Systems (NeurIPS), 2023
R. Wang,
Junchi Yan (correspondence), X. Yang
NCMNet: Neighbor Consistency Mining Network for Two-View Correspondence Pruning.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2022
R. Wang,
Junchi Yan (correspondence), X. Yang
Neural Graph Matching Network: Learning Lawler's Quadratic Assignment Problem with Extension to Hypergraph and Multiple-graph Matching.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2022, 44(9): 5261-5279
[arxiv] [project page]
R. Wang, Y. Zhang, Z. Guo (本科生), T. Chen (本科生), X. Yang,
Junchi Yan (correspondence).
LinSATNet: The Positive Linear Satisfiability Neural Networks.
International Conference on Machine Learning (ICML), 2023.
Y. Jin, Q. Bao, R. Wang,
Junchi Yan, Kun He.
CoNet: Complementary Encoding Networks for Solving Combinatorial Problems on Graph.
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023.
Q. Ren, Q. Bao (本科生), R. Wang,
Junchi Yan (correspondence).
Appearance and Structure Aware Robust Deep Visual Graph Matching: Attack, Defense and Beyond.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
Junchi Yan, S. Yang, E. Hancock.
Learning Graph Matching and Related Combinatorial Optimization Problems.
International Joint Conferences on Artificial Intelligence (IJCAI), 2020.
R. Wang, H. Hua, G. Liu, J. Zhang,
Junchi Yan (correspondence), F. Qi, S. Yang, X. Yang
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs.
Neural Information Processing Systems (NeurIPS), 2021
R. Wang,
Junchi Yan (correspondence), X. Yang.
Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network Learning.
Neural Information Processing Systems (NeurIPS), 2020
C. Liu, S. Zhang, X. Yang,
Junchi Yan (correspondence)
Self-supervised Learning of Visual Graph Matching.
European Conference on Computer Vision (ECCV), 2022.
L. Shi, H. Zhang (本科生), S. Shen, C. Meng, W. Wang,
Junchi Yan (correspondence).
BiQAP: Neural Bi-level Optimization-based Framework for Solving Quadratic Assignment Problems
.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2025.
J. Guo (本科生), S. Zhang, R. Wang, C. Liu, Junchi Yan (correspondence)
GMTR: Graph Matching Transformers.
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Y. He, Q. Gan, D. Wipf, G. Reinert,
Junchi Yan , M. Cucuringu.
GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks .
International Conference on Machine Learning (ICML), 2022.
T. Yu, R. Wang,
Junchi Yan (correspondence), B. Li.
Deep Latent Graph Matching.
International Conference on Machine Learning (ICML), 2021.
C. Li, F. Wei, W. Dong, X. Wang,
Junchi Yan (correspondence), X. Zhu, Q. Liu, X. Zhang.
Spatially Regularized Streaming Sensor Selection.
AAAI Conference on Artificial Intelligence (AAAI), 2016.
X. Yang, C. Deng, K. Wei,
Junchi Yan, W. Liu.
Adversarial Learning for Robust Deep Clustering.
Neural Information Processing Systems (NeurIPS), 2020
C. Liu, Z. Jiang, R. Wang, L. Huang, P. Lu,
Junchi Yan (correspondence)
Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching.
International Conference on Learning Representations (ICLR), 2023.
H. Lu, Z. Li (本科生), R. Wang, Q. Ren, X. Li, M. Yuan, J. Zeng, X. Yang,
Junchi Yan (correspondence)
ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs.
International Conference on Learning Representations (ICLR), 2023.
R. Wang, L. Shen, Y. Chen, X. Yang, D. Tao,
Junchi Yan (correspondence)
Towards One-shot Neural Combinatorial Optimization Solvers: Theoretical and Empirical Notes on the Cardinality-Constrained Case.
International Conference on Learning Representations (ICLR), 2023.
R. Wang, Z. Guo (本科生), S. Jiang (本科生), X. Yang,
Junchi Yan (correspondence).
Deep Learning of Partial Graph Matching via Differentiable Top-K.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
R. Wang, T. Zhang, T. Yu,
Junchi Yan (correspondence), X. Yang.
Combinatorial Learning of Graph Edit Distance via Dynamic Embedding.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
G. Wang, Q. Zhen,
Junchi Yan, L. Jiang.
Learning to Select Elements for Graphic Design.
ACM International Conference on Multimedia Retrieval (ICMR), 2020.
T. Yu, R. Wang,
Junchi Yan, B. Li
Learning deep graph matching with channel-independent embedding and Hungarian attention
International Conference on Learning Representations (ICLR), 2020.
R. Wang (本科生),
Junchi Yan (correspondence), X. Yang
Learning Combinatorial Embedding Networks for Deep Graph Matching
International Conference on Computer Vision (ICCV Oral), 2019.
AI for Science, Engineering and Arts (EDA, Crypto, Drug, PDE, Neuro, Arts):
Students (alumni): {EDA: Ruoyu Cheng, Yang Li, Xingbo Du, Ruizhe Zhong, Peiyu Wang, Jianyong Yuan et al.} & {Drug/Chem/Neuro: Nianzu Yang, Kaipeng Zeng, Huaijin Wu et al.} & {PDE: Mingquan Feng, Zelin Zhao et al.}
Junchi Yan, Y. Tang, H. Xiong, X. Ye, Y. Wang, Y. Qi (correspondence)
Tensor Network: from the Perspective of AI4Science and Science4AI.
International Jpoint Conference on Artificial Intelligence (IJCAI), 2025.
Fei Wu, Tao Shen, Thomas Bäck, Jingyuan Chen, Gang Huang, Yaochu Jin, Kun Kuang, Mengze Li, Cewu Lu, Jiaxu Miao, Yongwei Wang, Ying Wei, Fan Wu,
Junchi Yan,
Hongxia Yang, Yi Yang, Shengyu Zhang, Zhou Zhao, Yueting Zhuang, Yunhe Pan
Knowledge-Empowered, Collaborative, and Co-Evolving AI Models: The Post-LLM Roadmap.
(Engineering), 2024.
L. Shi, S. Zhang, X. Du, N. Yang,
Junchi Yan (correspondence)
DSBRouter: Solving Global Routing via Diffusion Schrodinger Bridge.
International Conference on Machine Learning (ICML), 2025.
M. Feng, W. Liao, Y. Huang (本科生), Y. Fu (本科生), Q. Zheng (本科生),
Junchi Yan (correspondence)
HEAP: Hyper Extended APDHG Operator for Constrained High-dim PDEs.
International Conference on Machine Learning (ICML), 2025.
M. Feng, Z. Chen, Y. Huang (本科生), Y. Liu (本科生),
Junchi Yan (correspondence)
Optimal Control Operator Perspective and a Neural Adaptive Spectral Method.
AAAI Conference on Artificial Intelligence (AAAI), 2025.
M. Feng, Y. Huang (本科生), Y. Liu (本科生), B. Jiang,
Junchi Yan (correspondence)
PhysPDE: Rethinking PDE Discovery and a Physical HYpothesis Selection Benchmark.
International Conference on Learning Representations (ICLR), 2025.
M. Feng, Y. Huang (本科生), Y. Liu (本科生), W. Liao, Y. Liu,
Junchi Yan (correspondence)
SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs.
International Conference on Learning Representations (ICLR), 2025.
R. Xia, M. Li, et al.,
Junchi Yan (correspondence), B. Zhang
GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-training.
International Conference on Learning Representations (ICLR), 2025.
Q. Xu, Junchi Yan et al.
Large Circuit Models: Opportunities and Challenges
SCIENCE CHINA Information Sciences, 2024
C. Liu, W. Wu, Y. Feng (本科生), Q. Cao, Junchi Yan (correspondence)
Towards General Loop Invariant Generation: A Benchmark of Programs with Memory Manipulation
Neural Information Processing Systems (NeurIPS), 2024 benchmark track
X. Zheng, L. Yang, C. Fan (本科生), H. Wu, X. Song (本科生), Junchi Yan (correspondence)
Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation
Neural Information Processing Systems (NeurIPS), 2024
R. Zhong, X. Du, S. Kai, Z. Tang, S. Xu, J. Hao, M. Yuan, Junchi Yan (correspondence)
FlexPlanner: Flexible 3D Floorplanning via Deep Reinforcement Learning in Hybrid Action Space with Multi-Modality Representation
Neural Information Processing Systems (NeurIPS), 2024
Z. Zhao, F. Fan, W. Liao,
Junchi Yan.
Grounding and Enhancing Grid-based Models for Neural Fields.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024 Best Paper Candidate
Y. Wang, Y. Xia,
Junchi Yan, Y. Yuan, H. Shen, X. Pan
ZeroBind: a protein-specific zero-shot predictor with subgraph matching for drug-target interactions.
Nature Communications (NC), 14 (1), 7861 2023.
M. Ma, Z. Jiang, T. Ma, X. Gao, J. Li, M. Liu,
Junchi Yan (correspondence), X. Jiang
Robust PUF Label Authentication System Synergistically Constructed by Hierarchical Pattern of Self-assembled Phase-Separation Encrypted Wrinkle and Deep Learning Model.
Advanced Functional Materials (AFM), 2405239, 2024.
N. Yang, K. Zeng, Y. Wu, H. Lu, Z. Yuan, F. Nie (本科生), Y. Li, S. Jiang, Y. Wang,
Junchi Yan (correspondence).
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation.
International Conference on Machine Learning (ICML) oral, 2024.
H. Wu, W. Liu, Y. Bian, J. Wu, N. Yang,
Junchi Yan (correspondence)
EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model.
International Conference on Learning Representations (ICLR), 2024.
R. Zhong, J. Ye, Z. Tang, S. Kai, M. Yuan, J. Hao,
Junchi Yan (correspondence)
PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Delay Learning and Attentional Cell Modeling.
AAAI Conference on Artificial Intelligence (AAAI), 2024.
X. Chen (本科生), L. Yang, R. Wang,
Junchi Yan (correspondence)
MixSATGen: Learning Graph Mixing for SAT Instance Generation.
International Conference on Learning Representations (ICLR), 2024.
P. Wang, A. Lu (本科生), J. Ye, X. Li, L. Chen, M. Yuan, J. Hao,
Junchi Yan (correspondence)
EasyMap: Improving Technology Mapping via Exploration-Enhanced Heuristics and Adaptive Sequencing.
IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023.
J. Yuan, J. Ye, Z. Tang, S. Kai, M. Yuan, J. Hao,
Junchi Yan (correspondence)
EasySO: Exploration-enhanced Reinforcement Learning for Logic Synthesis Sequence Optimization and a Comprehensive RL Environment.
IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023.
X. Du, R. Zhong, S. Kai, Z. Tang, S. Xu, J. Hao, M. Yuan,
Junchi Yan (correspondence).
JigsawPlanner: Jigsaw-like Floorplanner for Eliminating Whitespace and Overlap among Complex Rectilinear Modules.
IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2024.
Y. Li, X. Chen (本科生), W. Guo, X. Li, W. Luo, J. Huang, H. Zeng, M. Yuan,
Junchi Yan (correspondence)
HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2023.
R. Cheng (本科生),
Junchi Yan (correspondence).
On Joint Learning for Solving Placement and Routing in Chip Design.
Neural Information Processing Systems (NeurIPS), 2021
R. Cheng, X. Lv, Y. Li, J. Ye, J. Hao,
Junchi Yan (correspondence).
The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design.
Neural Information Processing Systems (NeurIPS), 2022
X. Du, C. Wang (本科生), R. Zhong (本科生),
Junchi Yan (correspondence).
HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection.
Neural Information Processing Systems (NeurIPS), 2023
N. Yang, K. Zeng (本科生), Q. Wu, X. Jia,
Junchi Yan (correspondence)
Learning Substructure Invariance for Out-of-Distribution Molecular Representations.
Neural Information Processing Systems (NeurIPS) (spotlight), 2022
N. Yang, K. Zeng (本科生), Q. Wu,
Junchi Yan (correspondence)
MoleRec: Enhancing Medication Combination Recommendation with Substructure-Aware Molecule Learning.
The ACM Web Conference (WWW), 2023
H. Xu,
Junchi Yan (correspondence), N. Persson, W. Lin, H. Zha.
Fractal Dimension Invariant Filtering and Its CNN-based Implementation.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
Y. Zhang, H. Li, S. Zhang, R. Wang, B. He, H. Dou,
Junchi Yan, Y. Zhang, F. Wu
LLMCO4MR: LLMs-aided Neural Combinatorial Optimization for Ancient Manuscript Restoration from Fragments with Case Studies on Dunhuang.
European Conference on Computer Vision (ECCV), 2024.
Y. Zhang, B. He, Y. Chen, H. Li, H. Yue, S. Zhang, H. Dou,
Junchi Yan, Z. Liu, Y. Zhang, F. Wu
PhiloGPT: A Philology-Oriented Large Language Model for Ancient Chinese Manuscripts with Dunhuang as Case Study
Empirical Methods in Natural Language Processing(EMNLP), 2024.
Y. Zhang, Z. Fang, X. Yang, S. Zhang, B. He, H. Dou,
Junchi Yan, Y. Zhang, F. Wu.
Reconnecting the Broken Civilization: Patchwork Integration of Fragments from Ancient Manuscripts.
ACM Multimedia (MM), 2023.
W. Liu, T. He, C. Gong, N. Zhang, H. Yang,
Junchi Yan.
Fine-Grained Music Plagiarism Detection: Revealing Plagiarists through Bipartite Graph Matching and a Comprehensive Large-Scale Dataset.
ACM Multimedia (MM), 2023.
Quantum Machine Learning (especially for Graphs):
Students (alumni): Ge Yan, Xinyu Ye, Yehui Tang, Hao Xiong, Wenjie Wu, Xudong Lu et al.
冯明泉, 唐叶辉, 陈志杰, 刘易洲 (本科生), 龙马彪 (本科生), 周子翔 (本科生), 王瑜含 (本科生),
严骏驰 (通讯)
从经典到量子:哈密顿神经网络研究综述.
人工智能 (AI-VIEW), 2024(5):53-70 [pdf], 2024
T. Bao, R. Zhong, X. Ye, Y. Tang,
Junchi Yan (correspondence)
QEM-Bench: Benchmarking Learning-based Quantum Error Mitigation and QEMFormer as a Multi-ranged Context Learning Baseline.
International Conference on Machine Learning (ICML), 2025.
R. Wang (本科生), Z. Xia, G. Yan,
Junchi Yan (correspondence)
QuanONet: Quantum Neural Operator with Application to Differential Equation.
International Conference on Machine Learning (ICML), 2025.
T. Bao, X. Ye, H. Ruan (本科生), C. Liu, W. Wu,
Junchi Yan (correspondence)
Beyond Circuit Connections: A Non-Message Passing Graph Transformer Approach for Quantum Error Mitigation.
International Conference on Learning Representations (ICLR), 2025.
X. Ye, H. Xiong, J. Huang (本科生), Z. Chen, J. Wang,
Junchi Yan (correspondence)
On Designing General and Expressive Quantum Graph Neural Networks with Applications to MILP Instance Representation.
International Conference on Learning Representations (ICLR), 2025.
G. Yan, W. Wu, Y. Chen (本科生), K. Pan (本科生), X. Lu, Z. Zhou, Y. Wang, R. Wang,
Junchi Yan (correspondence)
Quantum Circuit Synthesis and Compilation Optimization: Overview and Prospects.
arXiv preprint arXiv:2407.00736 (arXiv), 2024.
H. Wu, X. Ye, Junchi Yan (correspondence)
QVAE-Mole: The Quantum VAE with Spherical Latent Variable Learning for 3-D Molecule Generation
Neural Information Processing Systems (NeurIPS), 2024
G. Yan, M. Ran (本科生), R. Wang (本科生), K. Pan (本科生), Junchi Yan (correspondence)
Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz
Neural Information Processing Systems (NeurIPS), 2024
H. Xiong, Y. Tang, Y. He (本科生), W. Tan (本科生),
Junchi Yan (correspondence)
Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space.
International Conference on Learning Representations (ICLR), 2024.
G. Yan, H. Chen (本科生), K. Pan (本科生),
Junchi Yan (correspondence).
Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms.
International Conference on Learning Representations (ICLR), 2024.
Y. Tang, H. Xiong, N. Yang, T. Xiao,
Junchi Yan (correspondence).
Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark.
International Conference on Learning Representations (ICLR) spotlight, 2024.
Y. Tang, M. Long (本科生),
Junchi Yan (correspondence).
QuaDiM: A Conditional Diffusion Model For Quantum State Property Estimation
.
International Conference on Learning Representations (ICLR), 2025.
W. Wu, Y. Wang (本科生), G. Yan, Y. Zhao,
Junchi Yan (correspondence).
On Reducing the Execution Latency of Superconducting Quantum Processors via Quantum Program Scheduling.
IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2024.
Y. Tang, N. Yang, M. Long (本科生),
Junchi Yan (correspondence).
SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum System Certification.
International Conference on Machine Learning (ICML), 2024.
H. Xiong, Y. Tang, X. Ye,
Junchi Yan (correspondence)
Circuit Design and Efficient Simulation of Quantum Inner Product and Empirical Studies of Its Effect on Near-Term Hybrid Quantum-Classic Machine Learning.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
Y. Tang,
Junchi Yan (correspondence), G. Hu, B. Zhang, J. Zhou,
Recent progress and perspectives on quantum computing for finance.
Service Oriented Computing and Applications, 16, 227–229, 2022.
X. Ye, G. Yan,
Junchi Yan (correspondence)
VQNE: Variational Quantum Network Embedding with Application to Network Alignment.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2023.
G. Yan, Y. Tang,
Junchi Yan (correspondence).
Towards a Native Quantum Paradigm for Graph Representation Learning: a Sampling-based Recurrent Embedding Approach.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2022.
X. Ye, G. Yan,
Junchi Yan (correspondence).
Towards Quantum Machine Learning for Constrained Combinatorial Optimization: a Quantum QAP Solver.
International Conference on Machine Learning (ICML), 2023.
Y. Tang,
Junchi Yan (correspondence).
GraphQNTK: the Quantum Neural Tangent Kernel for Graph Data.
Neural Information Processing Systems (NeurIPS), 2022.
G. Yan, H. Wu,
Junchi Yan (correspondence).
Quantum 3D Graph Learning with Applications to Molecule Embedding.
International Conference on Machine Learning (ICML), 2023.
W. Wu, G. Yan, X. Lu (本科生), K. Pan (本科生),
Junchi Yan (correspondence).
QuantumDARTS: Differentiable Quantum Architecture Search for Variational Quantum Algorithms.
International Conference on Machine Learning (ICML), 2023.
X. Lu (本科生), K. Pan (本科生), G. Yan, J. Shan (本科生), W. Wu,
Junchi Yan (correspondence).
QAS-Bench: Rethinking Quantum Architecture Search and A Benchmark.
International Conference on Machine Learning (ICML), 2023.
Graph Learning (e.g. Backbones, especially for scalable and robust learning):
Students (alumni): Qitian Wu, Chenxiao Yang, Chao Chen, Haoyu Geng, Tianqi Zhang et al.
Q. Wu, D. Wipf,
Junchi Yan (correspondence)
Neural Message Passing Induced by Energy-Constrained Diffusion.
Journal of Machine Learning Research (JMLR) 2025
C. Chen, H. Geng, N. Yang, X. Yang, Junchi Yan (correspondence)
EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2024, 46 (12), 10845-10862
W. Zhao, Q. Wu, C. Yang, Junchi Yan (correspondence)
GeoMix: Towards Geometry-Aware Data Augmentation,
Knowledge Discovery and Data Mining Conference (SIGKDD), 2024
C. Yang, Q. Wu, D. Wipf, R. Sun, Junchi Yan (correspondence)
How Graph Neural Networks Learn: Lessons from Training Dynamics,
International Conference on Machine Learning (ICML), 2024
Q. Wu, F. Nie (本科生), C. Yang,
Junchi Yan (correspondence),
Learning Divergence Fields for Shift-Robust Graph Representations.
International Conference on Machine Learning (ICML), 2024.
Q. Wu, W. Zhao, C. Yang, H. Zhang, F. Nie (本科生), H. Jiang, Y. Bian, Junchi Yan (correspondence)
SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations
Neural Information Processing Systems (NeurIPS), 2023
T. Zhang, Q. Wu,
Junchi Yan (correspondence)
ScaleGCN: Efficient and Effective Graph Convolution via Channel-wise Scale Transformation
.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024, 35 (4), 4478-4490.
T. Zhang, Q. Wu,
Junchi Yan (correspondence).
Learning High-Order Graph Convolutional Networks via Adaptive Layerwise Aggregation Combination.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023, 34(8), 5144-5155.
C. Chen, D. Li,
Junchi Yan (correspondence), H. Huang, X. Yang.
Scalable and Explainable 1-Bit Matrix Completion via Graph Signal Processing and Analysis.
AAAI Conference on Artificial Intelligence (AAAI), 2021.
T. Bao, Q. Wu, Z. Jiang, Y. Chen, J. Sun,
Junchi Yan (correspondence).
Node Out-of-Distribution Detection Goes Neighborhood Shaping.
International Conference on Machine Learning (ICML), 2024.
Q. Wu, F. Nie (本科生), C. Yang, T. Bao,
Junchi Yan (correspondence)
Graph Out-of-distribution Generalization via Causal Intervention.
The ACM Web Conference (WWW), 2024 oral
Q. Wu, H. Zhang (本科生),
Junchi Yan (correspondence), D. Wipf
Handling Distribution Shifts on Graphs: An Invariance Perspective
International Conference on Learning Representations (ICLR), 2022.
C. Chen, H. Geng, G. Zeng, Z. Han, H. Chai, X. Yang,
Junchi Yan (correspondence),
Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution.
International Conference on Learning Representations (ICLR), 2023.
H. Geng, C. Chen, Y. He, G. Zeng, Z. Han, H. Chai,
Junchi Yan (correspondence)
Pyramid Graph Neural Network: a Graph Sampling and Filtering Approach for Multi-scale Disentangled Representations.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2023.
W. Zhao, Q. Wu, C. Yang,
Junchi Yan (correspondence)
GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2023.
Q. Wu, Y. Chen, C. Yang,
Junchi Yan (correspondence),
Energy-based Out-of-Distribution Detection for Graph Neural Networks.
International Conference on Learning Representations (ICLR), 2023.
Q. Wu, C. Yang, W. Zhao, Y. He, D. Wipf,
Junchi Yan (correspondence),
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion.
International Conference on Learning Representations (ICLR), 2023 (spotlight).
D. Lao (本科生), X. Yang (本科生), Q. Wu,
Junchi Yan (correspondence).
Variational Inference for Training Graph Neural Networks in Low-Data Regime through Joint Structure-Label Estimation.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2022.
C. Yang, Q. Wu, J. Wang,
Junchi Yan
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and Multi-Layer Perceptrons
.
International Conference on Learning Representations (ICLR), 2023.
Q. Wu, W. Zhao (本科生), Z. Li (本科生), D. Wipf,
Junchi Yan (correspondence).
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification.
Neural Information Processing Systems (NeurIPS) (spotlight), 2022
Z. Li (本科生), Q. Wu, F. Nie (本科生),
Junchi Yan (correspondence).
GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs.
Neural Information Processing Systems (NeurIPS), 2022
C. Yang, Q. Wu,
Junchi Yan (correspondence).
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks.
Neural Information Processing Systems (NeurIPS), 2022.
Discrete Time Space (Time Series) Learning:
Students (alumni): Yunhao Zhang, Longyuan Li et al.
Q. Wen, T. Zhou, C. Zhang, W. Chen, Z. Ma,
Junchi Yan, L. Sun.
Transformers in Time Series: A Survey.
International Joint Conferences on Artificial Intelligence (IJCAI), 2023.
Y. Zhang, M. Liu (本科生), S. Zhou (本科生),
Junchi Yan (correspondence).
UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis.
International Conference on Machine Learning (ICML), 2024.
Y. Zhang,
Junchi Yan (correspondence)
Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting.
International Conference on Learning Representations (ICLR), 2023 (oral).
N. Zhang,
Junchi Yan (correspondence), Y. Zhou.
Weakly-supervised Audio Source Separation via Spectrum Energy Preserved Wasserstein Learning.
International Joint Conferences on Artificial Intelligence (IJCAI), 2018.
Junchi Yan, C. Tian, J. Huang, F. Albertao.
Incremental Dictionary Learning for Fault Detection with Applications to Oil Pipeline Leakage Detection.
IET Electronics Letters (EL), 2011, 47 (21), 1198-1199.
L. Li, J. Yao, L. K. Wenliang, T. He, T. Xiao,
Junchi Yan (correspondence), D. Wipf, Z. Zhang.
GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction.
Neural Information Processing Systems (NeurIPS), 2021
L. Li,
Junchi Yan (correspondence), Y. Zhang (本科生), J. Zhang (本科生), J. Bao, Y. Jin, X. Yang.
Learning Generative RNN-ODE for Collaborative Time-Series and Event Sequence Forecasting.
IEEE Transactions on Knowledge Discovery and Data Engineering (TKDE), 35(7): 7118-7137, 2023
L. Li,
Junchi Yan (correspondence), Q. Wen, Y. Jin, X. Yang
Learning Robust Deep State Space for Unsupervised Anomaly Detection in Contaminated Time-Series.
IEEE Transactions on Knowledge Discovery and Data Engineering (TKDE), 35(6): 6058-6072, 2023
L. Li,
Junchi Yan (correspondence), H. Wang, Y. Jin.
Anomaly Detection of Time Series with Smoothness-Inducing Sequential Variational Auto-Encoder.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021, 32 (3), 1177-1191.
C. Yang, Q. Wu, Q. Wen, Z. Zhou, L. Sun,
Junchi Yan (correspondence).
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment.
Neural Information Processing Systems (NeurIPS), 2022
L. Li,
Junchi Yan (correspondence), X. Yang, Y. Jin.
Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting.
International Joint Conferences on Artificial Intelligence (IJCAI), 2019.
Continuous Time Space (Temporal Point Process) Learning:
Students (alumni): Yunhao Zhang, Mingquan Feng, Chao Chen, Shuai Xiao, Weichang Wu, Fangyu Ding et al.
Q. Wu, Z. Zhang, X. Gao,
Junchi Yan, G. Chen.
Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling.
Neural Information Processing Systems (NeurIPS), 2019
C. Chen, D. Li,
Junchi Yan (correspondence), X. Yang.
Modeling Dynamic User Preference via Dictionary Learning for Sequential Recommendation.
IEEE Transactions on Knowledge Discovery and Data Engineering (TKDE), 2022, 34(11): 5446-5458.
S. Li, M. Feng (本科生), L. Wang, A. Essofi, Y. Cao,
Junchi Yan , L. Song
Explaining Point Processes by Learning Interpretable Temporal Logic Rules.
International Conference on Learning Representations (ICLR), 2022.
S. Xiao,
Junchi Yan (correspondence), M. Farajtabar, L. Song, X. Yang, H. Zha.
Learning Time Series Associated Event Sequences with Recurrent Point Process Networks.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019, 30(10): 3124-3136.
W. Wu,
Junchi Yan (correspondence), X. Yang, H. Zha.
Discovering Temporal Patterns for Event Sequence Clustering via Policy Mixture Model.
IEEE Transactions on Knowledge Discovery and Data Engineering (TKDE), 2022, 34(2): 573-586.
W. Wu,
Junchi Yan (correspondence), X. Yang, H. Zha.
Decoupled Learning for Factorial Marked Temporal Point Processes.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2018.
Junchi Yan, X. Liu, L. Shi, C. Li, H. Zha.
Improving Maximum Likelihood Estimation of Temporal Point Process via Discriminative and Adversarial Learning.
International Joint Conferences on Artificial Intelligence (IJCAI), 2018.
S. Xiao, H. Xu,
Junchi Yan (correspondence), M. Farajtabar, X. Yang, L. Song, H. Zha.
Learning Conditional Generative Models for Temporal Point Processes.
AAAI Conference on Artificial Intelligence (AAAI), 2018.
S. Xiao, M. Farajtabar, X. Ye,
Junchi Yan, L. Song, H. Zha.
Wasserstein Learning of Deep Generative Point Process Models.
Neural Information Processing Systems (NIPS), 2017.
Junchi Yan, S. Xiao, C. Li, B. Jin, X. Wang, B. Ke, X. Yang, H. Zha.
Modeling Contagious Merger and Acquisition via Point Processes with a Profile Regression Prior.
International Joint Conferences on Artificial Intelligence (IJCAI), 2016.
C. Chen, H. Geng, N. Yang,
Junchi Yan (correspondence), D. Xue, J. Yu, X. Yang.
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation.
International Conference on Machine Learning (ICML), 2021.
Junchi Yan, C. Zhang, H. Zha, M. Gong, C. Sun, J. Huang, S. Chu, X. Yang.
On Machine Learning towards Predictive Sales Pipeline Analytics.
AAAI Conference on Artificial Intelligence (AAAI), 2015.
Junchi Yan, Y. Wang, K. Zhou, J. Huang, C. Tian, H. Zha, W. Dong.
Towards Effective Prioritizing Water Pipe Replacement and Rehabilitation.
International Joint Conferences on Artificial Intelligence (IJCAI), 2013.
X. Liu,
Junchi Yan (correspondence), S. Xiao, X. Wang, H. Zha, S. Chu.
On Predictive Patent Valuation: Forecasting Patent Citations and Their Types.
AAAI Conference on Artificial Intelligence (AAAI), 2017.
S. Xiao,
Junchi Yan (correspondence), X. Yang, H. Zha, S. Chu.
Modeling the Intensity Function of Point Process via Recurrent Neural Networks.
AAAI Conference on Artificial Intelligence (AAAI), 2017.
S. Xiao,
Junchi Yan (correspondence), C. Li, B. Jin, X. Wang, H. Zha, X. Yang, S. Chu.
On Modeling and Predicting Individual Paper Citation Count over Time.
International Joint Conferences on Artificial Intelligence (IJCAI), 2016.
Y. Zhang,
Junchi Yan (correspondence), X. Zhang, J. Zhou, X. Yang
Learning Mixture of Neural Temporal Point Processes for Multi-dimensional Event Sequence Clustering.
International Joint Conferences on Artificial Intelligence (IJCAI), 2022.
Y. Zhang (本科生),
Junchi Yan (correspondence).
Neural Relation Inference for Multi-dimensional Temporal Point Processes via Message Passing Graph.
International Joint Conferences on Artificial Intelligence (IJCAI), 2021.
F. Ding,
Junchi Yan (correspondence), H. Wang
c-NTPP: Learning Cluster-aware Neural Temporal Point Process.
AAAI Conferenc on Artificial Intelligence (AAAI), 2023.
X. Wang, S. Chen, Y. He, M. Wang, Q. Gan,
Junchi Yan
CEP3: Community Event Prediction with Neural Point Process on Graph.
The First Learning on Graphs Conference(LoG), 2023.
L. Li, J. Zhang (本科生),
Junchi Yan (correspondence), Y. Jin, Y. Zhang (本科生), Y. Duan, G. Tian.
Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting.
AAAI Conference on Artificial Intelligence (AAAI), 2021.
Automatic Neural Architecture Search and Optimization:
Students (alumni): Xiaoxing Wang, Zhexi Zhang et al.
X. Wang, Z. Lian, J. Lin, C. Xue,
Junchi Yan (correspondence)
DIY Your EasyNAS for Vision: Convolution Operation Merging, Map Channel Reducing, and Search Space to Supernet Conversion Tooling.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023: 45(11), 13974 - 13990
X. Wang, X. Qin (本科生), X. Yang, Junchi Yan
ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization
Neural Information Processing Systems (NeurIPS), 2024
B. Zhang (本科生), X. Wang, X. Qin (本科生),
Junchi Yan (correspondence).
Boosting Order-Preserving and Transferability for Neural Architecture Search: a Joint Architecture Refined Search and Fine-tuning Approach.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
X. Wang, X. Chu, Y. Fan, Z. Zhang, B. Zhang, X. Wei, X. Yang,
Junchi Yan (correspondence)
ROME: Robustifying Memory-Efficient NAS via Topology Disentanglement and Gradient Accumulation.
IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
X. Wang, W. Guo (本科生), J. Su, X. Yang,
Junchi Yan (correspondence)
ZARTS: On Zero-order Optimization for Neural Architecture Search.
Neural Information Processing Systems (NeurIPS), 2022
C. Xue, X. Wang,
Junchi Yan (correspondence), Y. Hu, X. Yang, K. Sun.
Rethinking Bi-Level Optimization in Neural Architecture Search: a Gibbs Sampling Perspective.
AAAI Conference on Artificial Intelligence (AAAI), 2021.
X. Chu, X. Wang, B. Zhang, S. Lu, X. Wei,
Junchi Yan
DARTS-: Robustly Stepping out of Performance Collapse Without Indicators.
International Conference on Learning Representations (ICLR), 2021.
X. Wang, J. Lin, J. Zhao, X. Yang,
Junchi Yan (correspondence).
EAutoDet: Efficient Architecture Search for Object Detection.
European Conference on Computer Vision (ECCV), 2022.
C. Xue,
Junchi Yan, R. Yan, S. Chu, Y. Lin, Y. Hu.
Transferable AutoML by Model Sharing over Grouped Datasets.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
C. Xue, X. Wang,
Junchi Yan, C. Li.
A Max-Flow based Approach for Neural Architecture Search
.
European Conference on Computer Vision (ECCV), 2022.
Z. Zhang, W. Zhu,
Junchi Yan, P. Gao and G. Xie
Automatic Student Network Search for Knowledge Distillation.
International Conference on Pattern Recognition (ICPR), 2020.
X. Wang, C. Xue,
Junchi Yan (correspondence), X. Yang, Y. Hu, K. Sun.
MergeNAS: Merge Operations into One for Differentiable Architecture Search.
International Joint Conferences on Artificial Intelligence (IJCAI), 2020.
Classic Algorithms for Graph and Combinatorial Optimization:
Students (alumni): Tianshu Yu (ASU), Zetian Jiang, Tianzhe Wang et al.
严骏驰, 杨小康
计算机视觉中图匹配研究进展: 从二图匹配迈向多图匹配.
控制理论与应用 (CCTA), 2018年第十二期 [pdf], 2018
C. Liu, C. Lou (本科生), R. Wang, A. Xi (本科生), L. Shen,
Junchi Yan (correspondence).
Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning.
International Conference on Machine Learning (ICML), 2022.
Z. Jiang (本科生), T. Wang (本科生),
Junchi Yan (correspondence)
Unifying Offline and Online Multi-graph Matching via Finding Shortest Paths on Supergraph.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021, 43(10): 3648-3663
Junchi Yan, M. Cho, H. Zha, X. Yang, S. Chu
Multi-Graph Matching via Affinity Optimization with Graduated Consistency Regularization.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016, 38(6): 1228-1242
code
Junchi Yan, C. Li, Y. Li, G. Cao
Adaptive Discrete Hypergraph Matching.
IEEE Transactions on Cybernetics (TCYB), 2018, 48(2): 765-779
Junchi Yan, J. Wang, H. Zha, X. Yang, S. Chu.
Consistency-Driven Alternating Optimization for Multigraph Matching: A Unified Approach.
IEEE Transactions on Image Processing (TIP), 2015, 24(3): 994-1009.
code
Junchi Yan, Z. Ren, H. Zha, S. Chu.
A Constrained Clustering based Approach for Matching a Collection of Feature Sets,.
IEEE International Conference on Pattern Recognition (ICPR), 2016.
Junchi Yan, X. Yin, W. Lin, C. Deng, H. Zha, X. Yang.
A Short Survey of Recent Advances in Graph Matching.
ACM International Conference on Multimedia Retrieval (ICMR oral), 2016.
T. Yu,
Junchi Yan, W. Liu, B. Li.
Incremental Multi-graph Matching via Diversity and Randomness based Graph Clustering
.
European Conference on Computer Vision (ECCV), 2018.
Junchi Yan, Y. Li, W. Liu, H. Zha, X. Yang, S. Chu.
Graduated Consistency-regularized Optimization for Multi-graph Matching.
European Conference on Computer Vision (ECCV), 2014.
Junchi Yan, Y. Tian, H. Zha, X. Yang, Y. Zhang, S. Chu.
Joint Optimization for Consistent Multiple Graph Matching.
IEEE International Conference on Computer Vision (ICCV), 2013.
Y. Tian,
Junchi Yan (correspondence), H. Zhang, Y. Zhang, X. Yang, H. Zha.
On the Convergence of Graph Matching: Graduated Assignment Revisited.
European Conference on Computer Vision (ECCV), 2012.
T. Yu,
Junchi Yan (correspondence), J. Zhao, B. Li.
Joint Cuts and Matching of Partitions in One Graph.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
T. Yu,
Junchi Yan, B. Li
Determinant Regularization for Gradient-Efficient Graph Matching.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
T. Wang (本科生), Z. Jiang (本科生),
Junchi Yan (correspondence).
Clustering-aware Multiple Graph Matching via Decayed Pairwise Matching Composition.
AAAI Conference on Artificial Intelligence (AAAI), 2020.
Z. Chen (本科生), Z. Xie (本科生),
Junchi Yan (correspondence), Y. Zheng, X. Yang.
Layered Neighborhood Expansion for Incremental Multiple Graph Matching.
European Conference on Computer Vision (ECCV), 2020.
Junchi Yan, H. Xu, H. Zha, X. Yang, S. Chu.
A Matrix Decomposition Perspective to Multiple Graph Matching.
IEEE International Conference on Computer Vision (ICCV), 2015.
T. Yu,
Junchi Yan, Y. Wang, W. Liu, B. Li.
Generalizing Graph Matching beyond Quadratic Assignment Model.
Neural Information Processing Systems (NIPS), 2018.
Junchi Yan, C. Zhang, H. Zha, W. Liu, X. Yang, S. Chu.
Discrete Hyper-graph Matching.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
Junchi Yan, J. Wang, H. Zha, X. Yang, S. Chu.
Multi-view Point Registration via Alternating Optimization.
AAAI Conference on Artificial Intelligence (AAAI), 2015.
Visual (Rotating) Object Detection:
Students (alumni): Xue Yang et al.
杨学,
严骏驰 (通讯作者)
基于特征对齐和高斯表征的视觉有向目标检测.
中国科学: 信息科学 (SSI), 2023, 53(11):2250 [pdf], 2023
X. Yang,
Junchi Yan (correspondence)
On the Arbitrary-Oriented Object Detection: Classification based Approaches Revisited.
International Journal of Computer Vision (IJCV) 130(5), 1340–1365, 2022
[project page]
Y. Yi, X. Yang, Y. Li, Z. Han, F. Da,
Junchi Yan (correspondence)
Wholly-WOOD: Wholly Leveraging Diversiffed-quality Labels for Weakly-supervised Oriented Object Detection.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025
[project page]
X. Yang,
Junchi Yan (correspondence), W. Liao, X. Yang, J. Tang, T. He
SCRDet++: Detecting Small, Cluttered and Rotated Objects via Instance-Level Feature Denoising and Rotation Loss Smoothing.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(2), 2384-2399, 2023
[project page]
X. Yang, G. Zhang, X. Yang, Y. Zhou, W. Wang, T. He, J. Tang,
Junchi Yan (correspondence)
Detecting Rotated Objects as Gaussian Distributions and Its 3-D Generalization.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 45(4): 4335-4354, 2023
Y. Zeng, Y. Chen, X. Yang, Q. Li,
Junchi Yan
ARS-DETR: Aspect Ratio-Sensitive Detection Transformer for Aerial Oriented Object Detection.
IEEE Transactions on Geoscience and Remote Sensing (TGRS) 62: 1-15, 2024
Y. Yu, B. Ren, P. Zhang, M. Liu, et al.
Junchi Yan, X. Yang
Point2RBox-v2: Rethinking Point-supervised Oriented Object Detection with Spatial Layout Among Instances.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
J. Luo, X. Yang, Y. Yu, Q. Li,,
Junchi Yan, Y. Li.
PointOBB: Learning Oriented Object Detection via Single Point Supervision.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
Y. Yu, X. Yang, Q. Li, F. Da, J. Dai, Y. Qiao,
Junchi Yan (correspondence).
Point2RBox: Combine Knowledge from Synthetic Visual Patterns for End-to-end Oriented Object Detection with Single Point Supervision.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
Z. Xiao, G. Yang, X. Yang, T. Mu,
Junchi Yan, S. Hu.
Theoretically Achieving Continuous Representation of Oriented Bounding Boxes.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
X. Yang, Y. Zhou, Junchi Yan (correspondence)
AlphaRotate: A rotation detection benchmark using tensorflow.
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Yi Yu, Xue Yang, Qingyun Li, Yue Zhou, Gefan Zhang, Feipeng Da, Junchi Yan (correspondence)
H2RBox-v2: Incorporating Symmetry for Boosting Horizontal Box Supervised Oriented Object Detection.
Neural Information Processing Systems (NeurIPS), 2023
X. Yang, Y. Zhou, G. Zhang, J. Yang, W. Wang,
Junchi Yan (correspondence), X. Zhang, Q. Tian
The KFIoU Loss for Rotated Object Detection.
International Conference on Learning Representations (ICLR), 2023.
X. Yang, G. Zhang, W. Li, Y. Zhou, X. Wang,
Junchi Yan (correspondence)
H2RBox: Horizonal Box Annotation is All You Need for Oriented Object Detection.
International Conference on Learning Representations (ICLR), 2023.
X. Yang, X. Yang, J. Yang, Q. Ming, W. Wang, Q. Tian,
Junchi Yan (correspondence).
Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence.
Neural Information Processing Systems (NeurIPS), 2021
X. Yang,
Junchi Yan (correspondence), Q. Ming, W. Wang, X. Zhang, Q. Tian.
Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss.
International Conference on Machine Learning (ICML), 2021.
X. Yang, L. Hou, Y. Zhou, W. Wang,
Junchi Yan (correspondence).
Dense Label Encoding for Boundary Discontinuity Free Rotation Detection.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
X. Yang,
Junchi Yan (correspondence).
Arbitrary-Oriented Object Detection with Circular Smooth Label.
European Conference on Computer Vision (ECCV), 2020.
Y. Zhou, X. Yang, G. Zhang,
Junchi Yan (correspondence) et al.
MMRotate: A Rotated Object Detection Benchmark using Pytorch.
ACM Multimedia (MM), 2022 (OS Track).
Q. Wen, X. Yang, S. Peng, M. Song,
Junchi Yan.
RSDet++: Point-based Modulated Loss for More Accurate Rotated Object Detection.
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022
W. Qian, X. Yang, S. Peng,
Junchi Yan, Y. Guo.
Learning Modulated Loss for Rotated Object Detection.
AAAI Conference on Artificial Intelligence (AAAI), 2021.
X. Yang,
Junchi Yan (correspondence), Z. Feng, T. He.
R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object.
AAAI Conference on Artificial Intelligence (AAAI), 2021.
X. Yang, J. Yang,
Junchi Yan (correspondence), Y. Zhang, T. Zhang, Z. Guo, X. Sun, K. Fu
SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects
International Conference on Computer Vision (ICCV), 2019.
X. Yu, P. Chen, D. Wu, N. Hassan, G. Li,
Junchi Yan, H. Shi, Q. Ye, Z. Han
Object Localization under Single Coarse Point Supervision.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
Efficient, Robust and Trustable AI:
Students (alumni): Ruoxi Chen, Haoxuan Wang, Yiting Chen, Ning Liao, Yucheng Luo, Huaqing Shao et al.
H. Wu, L. Li, H. Huang, T. Yi, J. Zhang, M. Yu,
Junchi Yan (correspondence)
HShare: Fast LLM Decoding by Hierarchical Key-Value Sharing.
International Conference on Learning Representations (ICLR), 2025.
Q. Wu, C. Yang,
Junchi Yan (correspondence).
Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach.
Neural Information Processing Systems (NeurIPS), 2021
H. Shao, L. Wang, Y. Wang, Q. Ren,
Junchi Yan (correspondence)
Certified Robustness on Visual Graph Matching via Searching Optimal Smoothing Range.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2024.
Q. Ren, Y. Chen, Y. Mo (本科生), Q. Wu,
Junchi Yan (correspondence).
DICE: Domain-attack Invariant Causal Learning for Improved Data Privacy Protection and Adversarial Robustness.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2022.
H. Shao, L. Wang,
Junchi Yan (correspondence)
Robustness Certification for Structured Prediction with General Inputs via Safe Region Modeling in the Semimetric Output Space.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2023.
M. Li, C. Deng, T. Li,
Junchi Yan, X. Gao, H. Huang
Towards Transferable Targeted Attack.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (spotlight), 2020.
R. Chen, Z. Li (本科生), J. Li, C. Wu,
Junchi Yan .
On Collective Robustness of Bagging Against Data Poisoning.
International Conference on Machine Learning (ICML), 2022.
H. Wang, Z. Yu, Y. Yue, A. Anandkumar, A. Liu,
Junchi Yan
Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach.
International Joint Conferences on Artificial Intelligence (IJCAI), 2023.
Y. Chen, Q. Ren,
Junchi Yan (correspondence).
Rethinking and Improving Robustness of Convolutional Neural Networks: a Shapley Value-based Approach in Frequency Domain.
Neural Information Processing Systems (NeurIPS) (spotlight), 2022
J. Hu, H. Zhong, G. Wu, F. Yang, S. Gong,
Junchi Yan
Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling.
European Conference on Computer Vision (ECCV), 2022.
J. Hu, H. Tuo, C. Wang, L. Qiao, H. Zhong,
Junchi Yan, Z. Jing, H. Leung.
Discriminative Partial Domain Adversarial Network.
European Conference on Computer Vision (ECCV), 2020.
R. Chen, J. Li,
Junchi Yan, P. Li, B. Sheng.
Input-specific Robustness Certification for Randomized Smoothing.
AAAI Conference on Artificial Intelligence (AAAI), 2022.
N. Liao, Y. Liu, X. Li, C. Lei, G. Wang, X. Hua,
Junchi Yan (correspondence).
CoHOZ: Contrastive Multimodal Prompt Tuning for Hierarchical Open-set Zero-shot Recognition.
ACM Multimedia (MM), 2022.
Y. Luo, Y. Zhang,
Junchi Yan (correspondence), W. Liu,
Generalizing Face Forgery Detection with High-frequency Features.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Z. Xiong, L. Li,
Junchi Yan, H. Wang, H. He, Y. Jin.
Differential Privacy with Variant-Noise for Gaussian Processes Classification.
Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2019.
G. Wang, X. Wu, Z. Liu,
Junchi Yan (correspondence).
Prompt-based Zero-shot Video Moment Retrieval.
ACM Multimedia (MM), 2022.
Y. Luo, J. Zhu, K. He, W. Chu, Y. Tai,
Junchi Yan (correspondence), C. Wang.
StyleFace: Towards Identity-Disentangled Face Generation on Megapixels.
European Conference on Computer Vision (ECCV), 2022.
Recommender Systems and Collaborative Filtering:
Students (alumni): Chao Chen, Qitian Wu, et al.
W. Xu, Q. Wu, R. Wang, M. Ha, Q. Ma, L. Chen, B. Han,
Junchi Yan (correspondence)
Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions.
The ACM Web Conference (WWW), 2024 oral
Q. Wu, H. Zhang, X. Gao,
Junchi Yan , H. Zha.
Towards Open-World Recommender Systems: A Model-based Collaborative Filtering Approach.
International Conference on Machine Learning (ICML), 2021.
C. Chen, D. Li, Q. Lv,
Junchi Yan (mentor), L. Shang, S. Chu.
GLOMA: Embedding Global Information in Local Matrix Approximation Models for Collaborative Filtering.
AAAI Conference on Artificial Intelligence (AAAI), 2017.
D. Li, C. Chen, Q. Lv,
Junchi Yan, L. Shang, S. Chu.
Low-Rank Matrix Approximation with Stability.
International Conference on Machine Learning (ICML), 2016.
C. Chen, D. Li, Q. Lv,
Junchi Yan (mentor), S. Chu, L. Shang.
MPMA: Mixture Probabilistic Matrix Approximation for Collaborative Filtering.
International Joint Conferences on Artificial Intelligence (IJCAI), 2016.
C. Chen, H. Zhang, D. Li,
Junchi Yan, X. Yang
Synergizing Local and Global Models for Matrix Approximation
.
ACM International Conference on Conference on Knowledge Management (CIKM), 2019.
Machine Learning Basics and Miscellaneous:
X. Qin (本科生), X. Wang,
Junchi Yan (correspondence)
Towards Consistent Multi-Task Learning: Unlocking the Potential of Task-Specific Parameters.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
X. Qin (本科生), X. Wang,
Junchi Yan (correspondence)
Revisiting Fairness in Multitask Learning: A Performance-Driven Approach for Variance Reduction.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
H. Lu, Y. Xie, X. Yang, Junchi Yan (correspondence)
Boundary Matters: A Bi-Level Active Finetuning Method
Neural Information Processing Systems (NeurIPS), 2024
J. Hu, J. Lin, Junchi Yan, S. Gong
Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation
Neural Information Processing Systems (NeurIPS), 2024
J. Sun, K. Li, R. Chen, J. Li, C. Wu, Y. Ding, Junchi Yan
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes,
International Conference on Learning Representations (ICLR), 2024
Y. Chen, Z. Zhou, Junchi Yan (correspondence)
Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory,
International Conference on Learning Representations (ICLR), 2024
Y. Chen, Q. Wu,
Junchi Yan (correspondence)
Regularizing Energy among Training Samples for Out-of-Distribution Generalization.
International Conference on Learning Representations (ICLR), 2025.
S. Sun, H. Lu, J. Li, Y. Xie, T. Li, X. Yang, L. Zhang,
Junchi Yan (correspondence)
Rethinking Classifier Re-Training in Long-Tailed Recognition: Label Over-Smooth Can Make It Balance.
International Conference on Learning Representations (ICLR), 2025.
Y. Hua, X. Wang, B. Jin, W. Li,
Junchi Yan, X. He, H. Zha
HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2021
C. Li, X. Wang, W. Dong,
Junchi Yan, Q. Liu, H. Zha
Joint Active Learning with Feature Selection via CUR Matrix Decomposition.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019, 41 (6), 1382-1396
Y. Li,
Junchi Yan, Y. Zhou, J. Yang.
Optimum Subspace Learning and Error Correction for Tensors.
European Conference on Computer Vision (ECCV), 2010.
X. Xie, H. Lu,
Junchi Yan, X. Yang, M. Tomizuka, W. Zhan
Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning Paradigm.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
W. Zhang,
Junchi Yan, X. Wang, H. Zha.
Deep Extreme Multi-Label Learning.
ACM International Conference on Multimedia Retrieval (ICMR oral), 2018.
S. Zhang (本科生), M. Liu (本科生),
Junchi Yan (correspondence).
The Diversified Ensemble Neural Network.
Neural Information Processing Systems (NeurIPS), 2020.
C. Li,
Junchi Yan (correspondence), F. Wei, W. Dong, Q. Liu, H. Zha.
Self-paced Multi-task Learning.
AAAI Conference on Artificial Intelligence (AAAI), 2017.
C. Li, F. Wei,
Junchi Yan (correspondence), X. Zhang, Q. Liu, H. Zha.
A Self-Paced Regularization Framework for Multi-Label Learning.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018, 29 (6), 2660-2666.
X. Yang, C. Deng, F. Zheng,
Junchi Yan, W. Liu.
Deep Spectral Clustering using Dual Autoencoder Network.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
A. Zhang, N. Li, J. Pu, J. Wang,
Junchi Yan, H. Zha.
τ-FPL: Tolerance-Constrained Learning in Linear Time.
AAAI Conference on Artificial Intelligence (AAAI), 2018.
J. Zhu, L. Shi,
Junchi Yan (correspondence), H. Zha.
AutoMix: Mixup Networks for Sample Interpolation via Cooperative Barycenter Learning.
European Conference on Computer Vision (ECCV), 2020.
Multi-agent System and Distributed Optimization:
Students (alumni): Wenhao Li (ECNU) et al.
X. Wang.
Junchi Yan, B. Jin., W. Li.
Distributed and Parallel ADMM for Structured Nonconvex Optimization Problem .
IEEE Transactions on Cybernetics (TCYB), 2021, 51(9): 4540-4552.
J. Sheng, X. Wang, B. Jin,
Junchi Yan , W. Li, T. H. Chang, J. Wang, H. Zha
Learning Structured Communication for Multi-agent Reinforcement Learning.
Autonomous Agents and Multi-Agent Systems (AAMAS) 2021
[arxiv]
W. Li, B. Jin, X. Wang,
Junchi Yan, H. Zha
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning.
Journal of Machine Learning Research (JMLR) 24(178): 1−75, 2023
[arxiv]
X. Wang, W. Zhang,
Junchi Yan, X. Yuan, H. Zha
On the Flexibility of Block Coordinate Descent for Large-Scale Optimization.
Neurocomputing (NC), 2018.
Generative Models, Optimal Transport and Self-supervised Learning:
Students (alumni): Yang Li, Shaofeng Zhang, Liangliang Shi and Xiaojiang Yang et al.
L. Shi, Z. Shi (本科生),
Junchi Yan (correspondence).
SelKD: Selective Knowledge Distillation via Optimal Transport Perspective
.
International Conference on Learning Representations (ICLR), 2025.
L. Shi, Y. Li, K. Zeng, Y. Tu,
Junchi Yan (correspondence).
Optimal Flow Transport and its Entropic Regularization: a GPU-friendly Matrix Iterative Algorithm for Flow Balance Satisfaction
.
International Conference on Learning Representations (ICLR), 2025.
S. Zhang, Q. Zhou, S. Wu, H. Tan, Z. Wang, J. Huang,
Junchi Yan (correspondence).
CR2PQ: Continuous Relative Rotary Positional Query for Dense Visual Representation Learning.
International Conference on Learning Representations (ICLR), 2025
R. Xia, H. Ye, J. Yuan, X. Yan, T. Chen, Junchi Yan (correspondence), B. Shi, B. Zhang
Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy
Neural Information Processing Systems (NeurIPS), 2024
L. Shi, J. Fan (本科生),
Junchi Yan (correspondence)
OT-CLIP: Understanding and Generalizing CLIP via Optimal Transport.
International Conference on Machine Learning (ICML), 2024.
S. Zhang, J. Huang, Q. Zhou, Z. Wang, F. Wang, J. Luo,
Junchi Yan (correspondence).
Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach.
International Conference on Learning Representations (ICLR), 2024
L. Shi, H. Zhen (本科生), G. Zhang (本科生), Junchi Yan (correspondence)
Relative Entropic Optimal Transport: a (Prior-aware) Matching Perspective to (Unbalanced) Classification
Neural Information Processing Systems (NeurIPS), 2023
L. Shi, Z. Shen (本科生),
Junchi Yan (correspondence)
Double-Bounded Optimal Transport for Advanced Clustering and Classification.
AAAI Conference on Artificial Intelligence (AAAI), 2024.
L. Shi, G. Zhang (本科生), H. Zhen (本科生), J. Fan,
Junchi Yan (correspondence).
Understanding and Generalizing Contrastive Learning from the Inverse Optimal Transport Perspective.
International Conference on Machine Learning (ICML), 2023.
S. Zhang, Q. Zhou, Z. Wang, F. Wang,
Junchi Yan (correspondence).
Patch-level Contrastive Learning via Positional Query for Visual Pre-training.
International Conference on Machine Learning (ICML), 2023.
S. Zhang, F. Zhu, R. Zhao,
Junchi Yan (correspondence)
Patch-Level Contrasting without Patch Correspondence for Accurate and Dense Contrastive Representation Learning.
International Conference on Learning Representations (ICLR), 2023.
S. Zhang, F. Zhu, R. Zhao,
Junchi Yan (correspondence)
Contextual Image Masking Modeling via Synergized Contrasting without View Augmentation for Faster and Better Visual Pretraining.
International Conference on Learning Representations (ICLR), 2023.
S. Zhang, L. Qiu, F. Zhu,
Junchi Yan (correspondence), H. Zhang, R. Zhao, H. Li, X. Yang,
Align Representations with Base: A New Approach to Self-Supervised Learning.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
S. Zhang, F. Zhu,
Junchi Yan (correspondence), R. Zhao, X. Yang
Zero-CL: Instance and Feature decorrelation for negative-free symmetric contrastive learning
International Conference on Learning Representations (ICLR), 2022.
X. Yang, Y. Wang, J. Sun, X. Zhang, S. Zhang, Z. Li,
Junchi Yan (correspondence)
Nonlinear ICA Using Volume-Preserving Transformations.
International Conference on Learning Representations (ICLR), 2022.
H. Zhang, Q. Wu,
Junchi Yan, D. Wipf, P. S. Yu,
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.
Neural Information Processing Systems (NeurIPS), 2021
S. Zhang, M. Liu,
Junchi Yan (correspondence), H. Zhang, L. Huang, P. Lu, X. Yang.
m-mix: Generating Hard Negatives via Multi-sample Mixing for Contrastive Learning.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2022.
X. Yang, C. Deng, Z. Dang, K. Wei,
Junchi Yan,
SelfSAGCN: Self-Supervised Semantic Alignment for Graph Convolution Network.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
Y. Li (本科生), Y. Mo (本科生), L. Shi,
Junchi Yan (correspondence).
Improving Generative Adversarial Networks via Adversarial Learning in Latent Space .
Neural Information Processing Systems (NeurIPS) (spotlight), 2022
Y. Li, L. Shi,
Junchi Yan
IID-GAN: an IID Sampling Perspective for Regularizing Mode Collapse.
International Joint Conferences on Artificial Intelligence (IJCAI), 2023.
X. Yang,
Junchi Yan (correspondence), Y. Cheng, Y. Zhang.
Learning Deep Generative Clustering via Mutual Information Maximization .
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 34(9): 6263-6275, 2023
Network Embedding:
Students (alumni): Hao Xiong and Xinbo Du et al.
H. Xiong,
Junchi Yan (correspondence), Z. Huang.
Learning Regularized Noise Contrastive Estimation for Robust Network Embedding.
IEEE Transactions on Knowledge Discovery and Data Engineering (TKDE), 35(5): 5017-5034, 2023
X. Du,
Junchi Yan (correspondence), R. Zhang, H. Zha.
Cross-network Skip-gram Embedding for Joint Network Alignment and Link Prediction.
IEEE Transactions on Knowledge Discovery and Data Engineering (TKDE), 2022, 34(3): 1080-1095.
code
H. Xiong,
Junchi Yan (correspondence).
BTWalk: Branching Tree Random Walk for Multi-order Structured Network Embedding.
IEEE Transactions on Knowledge Discovery and Data Engineering (TKDE), 2022, 34(8): 3611 - 3628.
H. Xiong,
Junchi Yan (correspondence), L. Pan.
Contrastive Multi-View Multiplex Network Embedding with Applications to Robust Network Alignment.
Knowledge Discovery and Data Mining Conference (SIGKDD), 2021.
X. Du,
Junchi Yan (correspondence), H. Zha.
Joint Link Prediction and Network Alignment via Cross-graph Embedding.
International Joint Conferences on Artificial Intelligence (IJCAI), 2019.
dataset
S. Yang, J. Tian, H. Zhang,
Junchi Yan (correspondence), H. He, Y. Jin.
TransMS: Knowledge Graph Embedding for Complex Relations by Multidirectional Semantics.
International Joint Conferences on Artificial Intelligence (IJCAI), 2019.