Zhu, Jun

299 publications

NeurIPS 2025 A Regularized Newton Method for Nonconvex Optimization with Global and Local Complexity Guarantees Yuhao Zhou, Jintao Xu, Bingrui Li, Chenglong Bao, Chao Ding, Jun Zhu

NeurIPS 2025 Audio Super-Resolution with Latent Bridge Models Chang Li, Zehua Chen, Liyuan Wang, Jun Zhu

AAAI 2025 DUSTED: Dual-Attention Enhanced Spatial Transcriptomics Denoiser Jun Zhu, Yifu Li, Zhenchao Tang, Cheng Chang

ICCV 2025 DeepMesh: Auto-Regressive Artist-Mesh Creation with Reinforcement Learning Ruowen Zhao, Junliang Ye, Zhengyi Wang, Guangce Liu, Yiwen Chen, Yikai Wang, Jun Zhu

ICLR 2025 Diffusion Bridge Implicit Models Kaiwen Zheng, Guande He, Jianfei Chen, Fan Bao, Jun Zhu

ICCV 2025 DimensionX: Create Any 3D and 4D Scenes from a Single Image with Decoupled Video Diffusion Wenqiang Sun, Shuo Chen, Fangfu Liu, Zilong Chen, Yueqi Duan, Jun Zhu, Jun Zhang, Yikai Wang

ICML 2025 Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model Is Secretly a GAN Discriminator Kaiwen Zheng, Yongxin Chen, Huayu Chen, Guande He, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang

ICLR 2025 Elucidating the Preconditioning in Consistency Distillation Kaiwen Zheng, Guande He, Jianfei Chen, Fan Bao, Jun Zhu

ICML 2025 FrameBridge: Improving Image-to-Video Generation with Bridge Models Yuji Wang, Zehua Chen, Chen Xiaoyu, Yixiang Wei, Jun Zhu, Jianfei Chen

CVPR 2025 Improving Accuracy and Calibration via Differentiated Deep Mutual Learning Han Liu, Peng Cui, Bingning Wang, Weipeng Chen, Yupeng Zhang, Jun Zhu, Xiaolin Hu

ICLR 2025 Masked Diffusion Models Are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling Kaiwen Zheng, Yongxin Chen, Hanzi Mao, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang

ICCV 2025 MeshAnything V2: Artist-Created Mesh Generation with Adjacent Mesh Tokenization Yiwen Chen, Yikai Wang, Yihao Luo, Zhengyi Wang, Zilong Chen, Jun Zhu, Chi Zhang, Guosheng Lin

ICLR 2025 On the Optimization and Generalization of Two-Layer Transformers with Sign Gradient Descent Bingrui Li, Wei Huang, Andi Han, Zhanpeng Zhou, Taiji Suzuki, Jun Zhu, Jianfei Chen

ICML 2025 Oscillation-Reduced MXFP4 Training for Vision Transformers Yuxiang Chen, Haocheng Xi, Jun Zhu, Jianfei Chen

ICLR 2025 PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidance Haohan Weng, Yikai Wang, Tong Zhang, C. L. Philip Chen, Jun Zhu

AAAI 2025 Pruning Large Language Models with Semi-Structural Adaptive Sparse Training Weiyu Huang, Yuezhou Hu, Guohao Jian, Jun Zhu, Jianfei Chen

ICLR 2025 RDT-1B: A Diffusion Foundation Model for Bimanual Manipulation Songming Liu, Lingxuan Wu, Bangguo Li, Hengkai Tan, Huayu Chen, Zhengyi Wang, Ke Xu, Hang Su, Jun Zhu

ICML 2025 RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers Min Zhao, Guande He, Yixiao Chen, Hongzhou Zhu, Chongxuan Li, Jun Zhu

ICLR 2025 ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing Ziteng Wang, Jun Zhu, Jianfei Chen

IJCAI 2025 Riding the Wave: Multi-Scale Spatial-Temporal Graph Learning for Highway Traffic Flow Prediction Under Overload Scenarios Xigang Sun, Jiahui Jin, Hancheng Wang, Xiangguo Sun, Xiaoliang Wang, Jun Zhu

ICLR 2025 Robust Representation Consistency Model via Contrastive Denoising Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Chaowei Xiao, Zhongjie Ba, Kui Ren, Jun Zhu, Anima Anandkumar

ICML 2025 STAIR: Improving Safety Alignment with Introspective Reasoning Yichi Zhang, Siyuan Zhang, Yao Huang, Zeyu Xia, Zhengwei Fang, Xiao Yang, Ranjie Duan, Dong Yan, Yinpeng Dong, Jun Zhu

ICLRW 2025 SageAttention2: Efficient Attention with Smoothing Q and Per-Thread Quantization Jintao Zhang, Haofeng Huang, Pengle Zhang, Jia Wei, Jun Zhu, Jianfei Chen

ICML 2025 SageAttention2: Efficient Attention with Thorough Outlier Smoothing and Per-Thread INT4 Quantization Jintao Zhang, Haofeng Huang, Pengle Zhang, Jia Wei, Jun Zhu, Jianfei Chen

NeurIPS 2025 SageAttention3: Microscaling FP4 Attention for Inference and an Exploration of 8-Bit Training Jintao Zhang, Jia Wei, Haoxu Wang, Pengle Zhang, Xiaoming Xu, Haofeng Huang, Kai Jiang, Jianfei Chen, Jun Zhu

ICLR 2025 SageAttention: Accurate 8-Bit Attention for Plug-and-Play Inference Acceleration Jintao Zhang, Jia Wei, Pengle Zhang, Jun Zhu, Jianfei Chen

NeurIPS 2025 Scaling Diffusion Transformers Efficiently via $\mu$P Chenyu Zheng, Xinyu Zhang, Rongzhen Wang, Wei Huang, Zhi Tian, Weilin Huang, Jun Zhu, Chongxuan Li

IJCAI 2025 Self-Consistent Model-Based Adaptation for Visual Reinforcement Learning Xinning Zhou, Chengyang Ying, Yao Feng, Hang Su, Jun Zhu

NeurIPS 2025 ShapeLLM-Omni: A Native Multimodal LLM for 3D Generation and Understanding Junliang Ye, Zhengyi Wang, Ruowen Zhao, Shenghao Xie, Jun Zhu

ICML 2025 SpargeAttention: Accurate and Training-Free Sparse Attention Accelerating Any Model Inference Jintao Zhang, Chendong Xiang, Haofeng Huang, Jia Wei, Haocheng Xi, Jun Zhu, Jianfei Chen

ICLRW 2025 SpargeAttn: Training-Free Sparse Attention Accelerating Any Model Inference Jintao Zhang, Chendong Xiang, Haofeng Huang, Jia Wei, Haocheng Xi, Jun Zhu, Jianfei Chen

ICLR 2025 Toward Guidance-Free AR Visual Generation via Condition Contrastive Alignment Huayu Chen, Hang Su, Peize Sun, Jun Zhu

ICML 2025 Visual Generation Without Guidance Huayu Chen, Kai Jiang, Kaiwen Zheng, Jianfei Chen, Hang Su, Jun Zhu

ICML 2024 Accelerating Transformer Pre-Training with 2:4 Sparsity Yuezhou Hu, Kang Zhao, Weiyu Huang, Jianfei Chen, Jun Zhu

NeurIPS 2024 Aligning Diffusion Behaviors with Q-Functions for Efficient Continuous Control Huayu Chen, Kaiwen Zheng, Hang Su, Jun Zhu

NeurIPS 2024 C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory Tianjiao Luo, Tim Pearce, Huayu Chen, Jianfei Chen, Jun Zhu

ECCV 2024 CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model Zhengyi Wang, Yikai Wang, Yifei Chen, Chendong Xiang, Shuo Chen, Dajiang Yu, Chongxuan Li, Hang Su, Jun Zhu

TMLR 2024 Calibrating Deep Ensemble Through Functional Variational Inference Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu

NeurIPS 2024 Consistency Diffusion Bridge Models Guande He, Kaiwen Zheng, Jianfei Chen, Fan Bao, Jun Zhu

AAAI 2024 DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization Wentse Chen, Shiyu Huang, Yuan Chiang, Tim Pearce, Wei-Wei Tu, Ting Chen, Jun Zhu

ICML 2024 DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu

NeurIPS 2024 Diffusion Models Are Certifiably Robust Classifiers Huanran Chen, Yinpeng Dong, Shitong Shao, Zhongkai Hao, Xiao Yang, Hang Su, Jun Zhu

ECCV 2024 DreamReward: Aligning Human Preference in Text-to-3D Generation Junliang Ye, Fangfu Liu, Qixiu Li, Zhengyi Wang, Yikai Wang, Xinzhou Wang, Yueqi Duan, Jun Zhu

ICLR 2024 Efficient Backpropagation with Variance Controlled Adaptive Sampling Ziteng Wang, Jianfei Chen, Jun Zhu

ICML 2024 Efficient Black-Box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior Shuyu Cheng, Yibo Miao, Yinpeng Dong, Xiao Yang, Xiao-Shan Gao, Jun Zhu

ICLR 2024 Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patches Lingxuan Wu, Xiao Yang, Yinpeng Dong, Liuwei Xie, Hang Su, Jun Zhu

CVPR 2024 Exploring the Transferability of Visual Prompting for Multimodal Large Language Models Yichi Zhang, Yinpeng Dong, Siyuan Zhang, Tianzan Min, Hang Su, Jun Zhu

ICML 2024 Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning Hengkai Tan, Songming Liu, Kai Ma, Chengyang Ying, Xingxing Zhang, Hang Su, Jun Zhu

ECCV 2024 Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, Hao Zhang, Jie Yang, Qing Jiang, Chunyuan Li, Jianwei Yang, Hang Su, Jun Zhu, Lei Zhang

NeurIPS 2024 Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model Min Zhao, Hongzhou Zhu, Chendong Xiang, Kaiwen Zheng, Chongxuan Li, Jun Zhu

ICLR 2024 InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image Jianhui Li, Shilong Liu, Zidong Liu, Yikai Wang, Kaiwen Zheng, Jinghui Xu, Jianmin Li, Jun Zhu

ICML 2024 Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization Haocheng Xi, Yuxiang Chen, Kang Zhao, Kai Jun Teh, Jianfei Chen, Jun Zhu

ECCV 2024 LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents Shilong Liu, Hao Cheng, Haotian Liu, Hao Zhang, Feng Li, Tianhe Ren, Xueyan Zou, Jianwei Yang, Hang Su, Jun Zhu, Lei Zhang, Jianfeng Gao, Chunyuan Li

NeurIPS 2024 MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models Yichi Zhang, Yao Huang, Yitong Sun, Chang Liu, Zhe Zhao, Zhengwei Fang, Yifan Wang, Huanran Chen, Xiao Yang, Xingxing Wei, Hang Su, Yinpeng Dong, Jun Zhu

NeurIPS 2024 Noise Contrastive Alignment of Language Models with Explicit Rewards Huayu Chen, Guande He, Lifan Yuan, Ganqu Cui, Hang Su, Jun Zhu

NeurIPS 2024 On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability Chenyu Zheng, Wei Huang, Rongzhen Wang, Guoqiang Wu, Jun Zhu, Chongxuan Li

JMLR 2024 Optimal Learning Policies for Differential Privacy in Multi-Armed Bandits Siwei Wang, Jun Zhu

NeurIPS 2024 PEAC: Unsupervised Pre-Training for Cross-Embodiment Reinforcement Learning Chengyang Ying, Zhongkai Hao, Xinning Zhou, Xuezhou Xu, Hang Su, Xingxing Zhang, Jun Zhu

NeurIPS 2024 PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs Zhongkai Hao, Jiachen Yao, Chang Su, Hang Su, Ziao Wang, Fanzhi Lu, Zeyu Xia, Yichi Zhang, Songming Liu, Lu Lu, Jun Zhu

ICLR 2024 Rethinking Model Ensemble in Transfer-Based Adversarial Attacks Huanran Chen, Yichi Zhang, Yinpeng Dong, Xiao Yang, Hang Su, Jun Zhu

ICML 2024 Robust Classification via a Single Diffusion Model Huanran Chen, Yinpeng Dong, Zhengyi Wang, Xiao Yang, Chengqi Duan, Hang Su, Jun Zhu

NeurIPS 2024 S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-Training Yuezhou Hu, Jun Zhu, Jianfei Chen

ICLR 2024 Score Regularized Policy Optimization Through Diffusion Behavior Huayu Chen, Cheng Lu, Zhengyi Wang, Hang Su, Jun Zhu

NeurIPS 2024 T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models Yibo Miao, Yifan Zhu, Lijia Yu, Jun Zhu, Xiao-Shan Gao, Yinpeng Dong

ICML 2024 Towards Efficient Exact Optimization of Language Model Alignment Haozhe Ji, Cheng Lu, Yilin Niu, Pei Ke, Hongning Wang, Jun Zhu, Jie Tang, Minlie Huang

NeurIPS 2024 Vidu4D: Single Generated Video to High-Fidelity 4D Reconstruction with Dynamic Gaussian Surfels Yikai Wang, Xinzhou Wang, Zilong Chen, Zhengyi Wang, Fuchun Sun, Jun Zhu

JMLR 2024 Virtual-Event-Based Posterior Sampling and Inference for Neyman-Scott Processes Chengkuan Hong, Christian R. Shelton, Jun Zhu

UAI 2023 A Constrained Bayesian Approach to Out-of-Distribution Prediction Ziyu Wang, Binjie Yuan, Jiaxun Lu, Bowen Ding, Yunfeng Shao, Qibin Wu, Jun Zhu

CVPR 2023 All Are Worth Words: A ViT Backbone for Diffusion Models Fan Bao, Shen Nie, Kaiwen Xue, Yue Cao, Chongxuan Li, Hang Su, Jun Zhu

CVPR 2023 Benchmarking Robustness of 3D Object Detection to Common Corruptions Yinpeng Dong, Caixin Kang, Jinlai Zhang, Zijian Zhu, Yikai Wang, Xiao Yang, Hang Su, Xingxing Wei, Jun Zhu

ICLR 2023 Bi-Level Physics-Informed Neural Networks for PDE Constrained Optimization Using Broyden's Hypergradients Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Jian Song, Ze Cheng

ACML 2023 Can Infinitely Wide Deep Nets Help Small-Data Multi-Label Learning? Guoqiang Wu, Jun Zhu

AAAI 2023 Certifiable Out-of-Distribution Generalization Nanyang Ye, Lin Zhu, Jia Wang, Zhaoyu Zeng, Jiayao Shao, Chensheng Peng, Bikang Pan, Kaican Li, Jun Zhu

ICML 2023 Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu

ICLR 2023 DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection Hao Zhang, Feng Li, Shilong Liu, Lei Zhang, Hang Su, Jun Zhu, Lionel Ni, Heung-Yeung Shum

NeurIPS 2023 DPM-Solver-V3: Improved Diffusion ODE Solver with Empirical Model Statistics Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu

AAAI 2023 DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding Shilong Liu, Shijia Huang, Feng Li, Hao Zhang, Yaoyuan Liang, Hang Su, Jun Zhu, Lei Zhang

ICCV 2023 Detection Transformer with Stable Matching Shilong Liu, Tianhe Ren, Jiayu Chen, Zhaoyang Zeng, Hao Zhang, Feng Li, Hongyang Li, Jun Huang, Hang Su, Jun Zhu, Lei Zhang

NeurIPS 2023 Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, Jun Zhu

ICLR 2023 Equivariant Energy-Guided SDE for Inverse Molecular Design Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu

ICML 2023 GNOT: A General Neural Operator Transformer for Operator Learning Zhongkai Hao, Zhengyi Wang, Hang Su, Chengyang Ying, Yinpeng Dong, Songming Liu, Ze Cheng, Jian Song, Jun Zhu

MLJ 2023 Heterogeneous Multi-Task Gaussian Cox Processes Feng Zhou, Quyu Kong, Zhijie Deng, Fengxiang He, Peng Cui, Jun Zhu

NeurIPS 2023 Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-Optimality Liyuan Wang, Jingyi Xie, Xingxing Zhang, Mingyi Huang, Hang Su, Jun Zhu

NeurIPSW 2023 How Robust Is Google's Bard to Adversarial Image Attacks? Yinpeng Dong, Huanran Chen, Jiawei Chen, Zhengwei Fang, Xiao Yang, Yichi Zhang, Yu Tian, Hang Su, Jun Zhu

ICML 2023 Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu

CVPRW 2023 Learning CLIP Guided Visual-Text Fusion Transformer for Video-Based Pedestrian Attribute Recognition Jun Zhu, Jiandong Jin, Zihan Yang, Xiaohao Wu, Xiao Wang

NeurIPS 2023 Learning Sample Difficulty from Pre-Trained Models for Reliable Prediction Peng Cui, Dan Zhang, Zhijie Deng, Yinpeng Dong, Jun Zhu

NeurIPS 2023 Memory Efficient Optimizers with 4-Bit States Bingrui Li, Jianfei Chen, Jun Zhu

ICML 2023 MultiAdam: Parameter-Wise Scale-Invariant Optimizer for Multiscale Training of Physics-Informed Neural Networks Jiachen Yao, Chang Su, Zhongkai Hao, Songming Liu, Hang Su, Jun Zhu

ICML 2023 NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Ze Cheng, Jun Zhu

ICLR 2023 Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling Huayu Chen, Cheng Lu, Chengyang Ying, Hang Su, Jun Zhu

IJCAI 2023 On the Reuse Bias in Off-Policy Reinforcement Learning Chengyang Ying, Zhongkai Hao, Xinning Zhou, Hang Su, Dong Yan, Jun Zhu

ICML 2023 One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shi Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, Jun Zhu

NeurIPS 2023 Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation Yilin Lyu, Liyuan Wang, Xingxing Zhang, Zicheng Sun, Hang Su, Jun Zhu, Liping Jing

CVPR 2023 PREIM3D: 3D Consistent Precise Image Attribute Editing from a Single Image Jianhui Li, Jianmin Li, Haoji Zhang, Shilong Liu, Zhengyi Wang, Zihao Xiao, Kaiwen Zheng, Jun Zhu

ICLR 2023 Preserving Pre-Trained Features Helps Calibrate Fine-Tuned Language Models Guande He, Jianfei Chen, Jun Zhu

NeurIPS 2023 ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu

ICML 2023 Revisiting Discriminative vs. Generative Classifiers: Theory and Implications Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu

ICML 2023 Stabilizing GANs’ Training with Brownian Motion Controller Tianjiao Luo, Ziyu Zhu, Jianfei Chen, Jun Zhu

NeurIPS 2023 Towards Accelerated Model Training via Bayesian Data Selection Zhijie Deng, Peng Cui, Jun Zhu

CVPR 2023 Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition Xiao Yang, Chang Liu, Longlong Xu, Yikai Wang, Yinpeng Dong, Ning Chen, Hang Su, Jun Zhu

NeurIPSW 2023 Towards a General Framework for Continual Learning with Pre-Training Liyuan Wang, Jingyi Xie, Xingxing Zhang, Hang Su, Jun Zhu

NeurIPS 2023 Training Transformers with 4-Bit Integers Haocheng Xi, ChangHao Li, Jianfei Chen, Jun Zhu

NeurIPS 2022 A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs Songming Liu, Hao Zhongkai, Chengyang Ying, Hang Su, Jun Zhu, Ze Cheng

NeurIPS 2022 Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng, Feng Zhou, Jun Zhu

NeurIPSW 2022 All Are Worth Words: A ViT Backbone for Score-Based Diffusion Models Fan Bao, Chongxuan Li, Yue Cao, Jun Zhu

ICLR 2022 Analytic-DPM: An Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang

CVPR 2022 AutoLoss-GMS: Searching Generalized Margin-Based SoftMax Loss Function for Person Re-Identification Hongyang Gu, Jianmin Li, Guangyuan Fu, Chifong Wong, Xinghao Chen, Jun Zhu

CVPR 2022 BE-STI: Spatial-Temporal Integrated Network for Class-Agnostic Motion Prediction with Bidirectional Enhancement Yunlong Wang, Hongyu Pan, Jun Zhu, Yu-Huan Wu, Xin Zhan, Kun Jiang, Diange Yang

ECCVW 2022 BadDet: Backdoor Attacks on Object Detection Shih-Han Chan, Yinpeng Dong, Jun Zhu, Xiaolu Zhang, Jun Zhou

ACML 2022 BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-Tuning Zhijie Deng, Jun Zhu

ECCV 2022 Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks Xiao Yang, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu

NeurIPS 2022 Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis Tim Pearce, Jong-Hyeon Jeong, Yichen Jia, Jun Zhu

IJCAI 2022 Cluster Attack: Query-Based Adversarial Attacks on Graph with Graph-Dependent Priors Zhengyi Wang, Zhongkai Hao, Ziqiao Wang, Hang Su, Jun Zhu

ECCV 2022 CoSCL: Cooperation of Small Continual Learners Is Stronger than a Big One Liyuan Wang, Xingxing Zhang, Qian Li, Jun Zhu, Yi Zhong

NeurIPS 2022 Confidence-Based Reliable Learning Under Dual Noises Peng Cui, Yang Yue, Zhijie Deng, Jun Zhu

ICLR 2022 DAB-DETR: Dynamic Anchor Boxes Are Better Queries for DETR Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi, Hang Su, Jun Zhu, Lei Zhang

NeurIPS 2022 DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

NeurIPS 2022 EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu

JMLR 2022 Efficient Inference for Dynamic Flexible Interactions of Neural Populations Feng Zhou, Quyu Kong, Zhijie Deng, Jichao Kan, Yixuan Zhang, Cheng Feng, Jun Zhu

ICML 2022 Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang

ICLR 2022 Exploring Memorization in Adversarial Training Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, Jun Zhu

NeurIPS 2022 Fast Instrument Learning with Faster Rates Ziyu Wang, Yuhao Zhou, Jun Zhu

ICML 2022 Fast Lossless Neural Compression with Integer-Only Discrete Flows Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang

ICML 2022 GSmooth: Certified Robustness Against Semantic Transformations via Generalized Randomized Smoothing Zhongkai Hao, Chengyang Ying, Yinpeng Dong, Hang Su, Jian Song, Jun Zhu

ECCV 2022 INT: Towards Infinite-Frames 3D Detection with an Efficient Framework Jianyun Xu, Zhenwei Miao, Da Zhang, Hongyu Pan, Kaixuan Liu, Peihan Hao, Jun Zhu, Zhengyang Sun, Hongmin Li, Xin Zhan

NeurIPS 2022 Isometric 3D Adversarial Examples in the Physical World Yibo Miao, Yinpeng Dong, Jun Zhu, Xiao-Shan Gao

ICML 2022 Maximum Likelihood Training for Score-Based Diffusion ODEs by High Order Denoising Score Matching Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

ICLR 2022 Memory Replay with Data Compression for Continual Learning Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu

ICML 2022 NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng, Jiaxin Shi, Jun Zhu

NeurIPSW 2022 On Equivalences Between Weight and Function-Space Langevin Dynamics Ziyu Wang, Yuhao Zhou, Ruqi Zhang, Jun Zhu

CVPR 2022 OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization Nanyang Ye, Kaican Li, Haoyue Bai, Runpeng Yu, Lanqing Hong, Fengwei Zhou, Zhenguo Li, Jun Zhu

NeurIPSW 2022 Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations Yingtao Luo, Qiang Liu, Yuntian Chen, Wenbo Hu, Tian Tian, Jun Zhu

AAAI 2022 Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model Jialian Li, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu

ICML 2022 Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang, Min Lin, Xiao Yang, Jun Zhu, Shuicheng Yan

ICML 2022 Thompson Sampling for (Combinatorial) Pure Exploration Siwei Wang, Jun Zhu

MLOSS 2022 Tianshou: A Highly Modularized Deep Reinforcement Learning Library Jiayi Weng, Huayu Chen, Dong Yan, Kaichao You, Alexis Duburcq, Minghao Zhang, Yi Su, Hang Su, Jun Zhu

IJCAI 2022 Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk Chengyang Ying, Xinning Zhou, Hang Su, Dong Yan, Ning Chen, Jun Zhu

CVPR 2022 Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu

NeurIPS 2022 ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints Yinpeng Dong, Shouwei Ruan, Hang Su, Caixin Kang, Xingxing Wei, Jun Zhu

NeurIPSW 2022 Why Are Conditional Generative Models Better than Unconditional Ones? Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu

AISTATS 2021 Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, Wipf David

AAAI 2021 A Bayesian Approach for Subset Selection in Contextual Bandits Jialian Li, Chao Du, Jun Zhu

NeurIPS 2021 AFEC: Active Forgetting of Negative Transfer in Continual Learning Liyuan Wang, Mingtian Zhang, Zhongfan Jia, Qian Li, Chenglong Bao, Kaisheng Ma, Jun Zhu, Yi Zhong

NeurIPS 2021 Accumulative Poisoning Attacks on Real-Time Data Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu

ICMLW 2021 Adversarial Semantic Contour for Object Detection Yichi Zhang, Zijian Zhu, Xiao Yang, Jun Zhu

ICLR 2021 Bag of Tricks for Adversarial Training Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu

ICCV 2021 Black-Box Detection of Backdoor Attacks with Limited Information and Data Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu

IJCAI 2021 Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu Yunsheng Zhang, Dong Yan, Bei Shi, Haobo Fu, Qiang Fu, Hang Su, Jun Zhu, Ning Chen

ICLR 2021 Efficient Inference of Flexible Interaction in Spiking-Neuron Networks Feng Zhou, Yixuan Zhang, Jun Zhu

ICLR 2021 Implicit Normalizing Flows Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu

AAAI 2021 Improving Generative Moment Matching Networks with Distribution Partition Yong Ren, Yucen Luo, Jun Zhu

CVPR 2021 Improving Transferability of Adversarial Patches on Face Recognition with Generative Models Zihao Xiao, Xianfeng Gao, Chilin Fu, Yinpeng Dong, Wei Gao, Xiaolu Zhang, Jun Zhou, Jun Zhu

AAAI 2021 Learning Task-Distribution Reward Shaping with Meta-Learning Haosheng Zou, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu

CVPR 2021 LiBRe: A Practical Bayesian Approach to Adversarial Detection Zhijie Deng, Xiao Yang, Shizhen Xu, Hang Su, Jun Zhu

ICLR 2021 MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering Tsung Wei Tsai, Chongxuan Li, Jun Zhu

CVPR 2021 ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu

NeurIPS 2021 On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms Shuyu Cheng, Guoqiang Wu, Jun Zhu

CVPR 2021 PVGNet: A Bottom-up One-Stage 3D Object Detector with Integrated Multi-Level Features Zhenwei Miao, Jikai Chen, Hongyu Pan, Ruiwen Zhang, Kaixuan Liu, Peihan Hao, Jun Zhu, Yang Wang, Xin Zhan

ICMLW 2021 Query-Based Adversarial Attacks on Graph with Fake Nodes Zhengyi Wang, Hao Zhongkai, Jun Zhu

NeurIPS 2021 Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization Guoqiang Wu, Chongxuan Li, Kun Xu, Jun Zhu

NeurIPS 2021 Scalable Quasi-Bayesian Inference for Instrumental Variable Regression Ziyu Wang, Yuhao Zhou, Tongzheng Ren, Jun Zhu

NeurIPS 2021 Stability and Generalization of Bilevel Programming in Hyperparameter Optimization Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang

ICMLW 2021 Strategically-Timed State-Observation Attacks on Deep Reinforcement Learning Agents You Qiaoben, Xinning Zhou, Chengyang Ying, Jun Zhu

ICCV 2021 Towards Face Encryption by Generating Adversarial Identity Masks Xiao Yang, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu, Yuefeng Chen, Hui Xue

ICMLW 2021 Towards Safe Reinforcement Learning via Constraining Conditional Value at Risk Chengyang Ying, Xinning Zhou, Dong Yan, Jun Zhu

CVPR 2021 Unsupervised Part Segmentation Through Disentangling Appearance and Shape Shilong Liu, Lei Zhang, Xiao Yang, Hang Su, Jun Zhu

ICML 2021 Variational (Gradient) Estimate of the Score Function in Energy-Based Latent Variable Models Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang

AISTATS 2020 A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models Ziyu Wang, Shuyu Cheng, Li Yueru, Jun Zhu, Bo Zhang

NeurIPS 2020 Adversarial Distributional Training for Robust Deep Learning Yinpeng Dong, Zhijie Deng, Tianyu Pang, Jun Zhu, Hang Su

NeurIPS 2020 Bi-Level Score Matching for Learning Energy-Based Latent Variable Models Fan Bao, Chongxuan Li, Kun Xu, Hang Su, Jun Zhu, Bo Zhang

NeurIPS 2020 Boosting Adversarial Training with Hypersphere Embedding Tianyu Pang, Xiao Yang, Yinpeng Dong, Kun Xu, Jun Zhu, Hang Su

NeurIPS 2020 Calibrated Reliable Regression Using Maximum Mean Discrepancy Peng Cui, Wenbo Hu, Jun Zhu

ECCV 2020 Defense Against Adversarial Attacks via Controlling Gradient Leaking on Embedded Manifolds Yueru Li, Shuyu Cheng, Hang Su, Jun Zhu

ECCV 2020 Design and Interpretation of Universal Adversarial Patches in Face Detection Xiao Yang, Fangyun Wei, Hongyang Zhang, Jun Zhu

NeurIPS 2020 Efficient Learning of Generative Models via Finite-Difference Score Matching Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu

UAI 2020 Exploration Analysis in Finite-Horizon Turn-Based Stochastic Games Jialian Li, Yichi Zhou, Tongzheng Ren, Jun Zhu

MLJ 2020 Foreword: Special Issue for the Journal Track of the 11th Asian Conference on Machine Learning (ACML 2019) Kee-Eung Kim, Jun Zhu

NeurIPS 2020 Further Analysis of Outlier Detection with Deep Generative Models Ziyu Wang, Bin Dai, David P. Wipf, Jun Zhu

NeurIPSW 2020 Further Analysis of Outlier Detection with Deep Generative Models Ziyu Wang, Bin Dai, David Wipf, Jun Zhu

ICLR 2020 Lazy-CFR: Fast and Near-Optimal Regret Minimization for Extensive Games with Imperfect Information Yichi Zhou, Tongzheng Ren, Jialian Li, Dong Yan, Jun Zhu

ECML-PKDD 2020 Learning Implicit Generative Models by Teaching Density Estimators Kun Xu, Chao Du, Chongxuan Li, Jun Zhu, Bo Zhang

ICLR 2020 Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang, Kun Xu, Jun Zhu

NeurIPS 2020 Multi-Label Classification: Do Hamming Loss and Subset Accuracy Really Conflict with Each Other? Guoqiang Wu, Jun Zhu

ICML 2020 Nonparametric Score Estimators Yuhao Zhou, Jiaxin Shi, Jun Zhu

ICLR 2020 Posterior Sampling for Multi-Agent Reinforcement Learning: Solving Extensive Games with Imperfect Information Yichi Zhou, Jialian Li, Jun Zhu

ICLR 2020 Rethinking SoftMax Cross-Entropy Loss for Adversarial Robustness Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu

ICLR 2020 SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models Yucen Luo, Alex Beatson, Mohammad Norouzi, Jun Zhu, David Duvenaud, Ryan P. Adams, Ricky T. Q. Chen

ICLR 2020 SVQN: Sequential Variational Soft Q-Learning Networks Shiyu Huang, Hang Su, Jun Zhu, Ting Chen

ICLR 2020 To Relieve Your Headache of Training an MRF, Take AdVIL Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang

ECCV 2020 Training Interpretable Convolutional Neural Networks by Differentiating Class-Specific Filters Haoyu Liang, Zhihao Ouyang, Yuyuan Zeng, Hang Su, Zihao He, Shu-Tao Xia, Jun Zhu, Bo Zhang

NeurIPS 2020 Understanding and Exploring the Network with Stochastic Architectures Zhijie Deng, Yinpeng Dong, Shifeng Zhang, Jun Zhu

ICML 2020 Understanding and Stabilizing GANs’ Training Dynamics Using Control Theory Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang

ICLR 2020 Unifying Graph Convolutional Networks as Matrix Factorization Zhaocheng Liu, Qiang Liu, Haoli Zhang, Jun Zhu

ICML 2020 VFlow: More Expressive Generative Flows with Variational Data Augmentation Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian

ICML 2020 Variance Reduction and Quasi-Newton for Particle-Based Variational Inference Michael Zhu, Chang Liu, Jun Zhu

NeurIPSW 2020 Variational (Gradient) Estimate of the Score Function in Energy-Based Latent Variable Models Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang

AAAI 2019 Combo-Action: Training Agent for FPS Game with Auxiliary Tasks Shiyu Huang, Hang Su, Jun Zhu, Ting Chen

AAAI 2019 Composite Binary Decomposition Networks You Qiaoben, Zheng Wang, Jianguo Li, Yinpeng Dong, Yu-Gang Jiang, Jun Zhu

AAAI 2019 Direct Training for Spiking Neural Networks: Faster, Larger, Better Yujie Wu, Lei Deng, Guoqi Li, Jun Zhu, Yuan Xie, Luping Shi

ICLR 2019 Function Space Particle Optimization for Bayesian Neural Networks Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang

NeurIPS 2019 Generative Well-Intentioned Networks Justin Cosentino, Jun Zhu

ICML 2019 Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu

NeurIPS 2019 Improving Black-Box Adversarial Attacks with a Transfer-Based Prior Shuyu Cheng, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu

NeurIPS 2019 Multi-Objects Generation with Amortized Structural Regularization Taufik Xu, Chongxuan Li, Jun Zhu, Bo Zhang

IJCAI 2019 Playing FPS Games with Environment-Aware Hierarchical Reinforcement Learning Shihong Song, Jiayi Weng, Hang Su, Dong Yan, Haosheng Zou, Jun Zhu

ICML 2019 Scalable Training of Inference Networks for Gaussian-Process Models Jiaxin Shi, Mohammad Emtiyaz Khan, Jun Zhu

AAAI 2019 Sparse Adversarial Perturbations for Videos Xingxing Wei, Jun Zhu, Sha Yuan, Hang Su

MLJ 2019 Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference Zhize Li, Tianyi Zhang, Shuyu Cheng, Jun Zhu, Jian Li

ICML 2019 Understanding MCMC Dynamics as Flows on the Wasserstein Space Chang Liu, Jingwei Zhuo, Jun Zhu

ICML 2019 Understanding and Accelerating Particle-Based Variational Inference Chang Liu, Jingwei Zhuo, Pengyu Cheng, Ruiyi Zhang, Jun Zhu

ICML 2018 A Spectral Approach to Gradient Estimation for Implicit Distributions Jiaxin Shi, Shengyang Sun, Jun Zhu

ICML 2018 Adversarial Attack on Graph Structured Data Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song

AAAI 2018 Collaborative Filtering with User-Item Co-Autoregressive Models Chao Du, Chongxuan Li, Yin Zheng, Jun Zhu, Bo Zhang

NeurIPS 2018 Graphical Generative Adversarial Networks Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang

ICLR 2018 Kernel Implicit Variational Inference Jiaxin Shi, Shengyang Sun, Jun Zhu

IJCAI 2018 Learning to Write Stylized Chinese Characters by Reading a Handful of Examples Danyang Sun, Tongzheng Ren, Chongxuan Li, Hang Su, Jun Zhu

ICML 2018 Max-Mahalanobis Linear Discriminant Analysis Networks Tianyu Pang, Chao Du, Jun Zhu

ICML 2018 Message Passing Stein Variational Gradient Descent Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, Bo Zhang

ACML 2018 Preface Jun Zhu, Ichiro Takeuchi

IJCAI 2018 Probabilistic Machine Learning: Models, Algorithms and a Programming Library Jun Zhu

ICML 2018 Racing Thompson: An Efficient Algorithm for Thompson Sampling with Non-Conjugate Priors Yichi Zhou, Jun Zhu, Jingwei Zhuo

AAAI 2018 Riemannian Stein Variational Gradient Descent for Bayesian Inference Chang Liu, Jun Zhu

AAAI 2018 Selective Verification Strategy for Learning from Crowds Tian Tian, Yichi Zhou, Jun Zhu

NeurIPS 2018 Semi-Crowdsourced Clustering with Deep Generative Models Yucen Luo, Tian Tian, Jiaxin Shi, Jun Zhu, Bo Zhang

NeurIPS 2018 Stochastic Expectation Maximization with Variance Reduction Jianfei Chen, Jun Zhu, Yee Whye Teh, Tong Zhang

ICML 2018 Stochastic Training of Graph Convolutional Networks with Variance Reduction Jianfei Chen, Jun Zhu, Le Song

NeurIPS 2018 Towards Robust Detection of Adversarial Examples Tianyu Pang, Chao Du, Yinpeng Dong, Jun Zhu

AAAI 2018 Towards Training Probabilistic Topic Models on Neuromorphic Multi-Chip Systems Zihao Xiao, Jianfei Chen, Jun Zhu

AAAI 2018 Understanding Human Behaviors in Crowds by Imitating the Decision-Making Process Haosheng Zou, Hang Su, Shihong Song, Jun Zhu

IJCAI 2017 Distributed Accelerated Proximal Coordinate Gradient Methods Yong Ren, Jun Zhu

IJCAI 2017 Forecast the Plausible Paths in Crowd Scenes Hang Su, Jun Zhu, Yinpeng Dong, Bo Zhang

ICML 2017 Identify the Nash Equilibrium in Static Games with Random Payoffs Yichi Zhou, Jialian Li, Jun Zhu

CVPR 2017 Improving Interpretability of Deep Neural Networks with Semantic Information Yinpeng Dong, Hang Su, Jun Zhu, Bo Zhang

IJCAI 2017 Improving Learning-from-Crowds Through Expert Validation Mengchen Liu, Liu Jiang, Junlin Liu, Xiting Wang, Jun Zhu, Shixia Liu

AAAI 2017 Learning Attributes from the Crowdsourced Relative Labels Tian Tian, Ning Chen, Jun Zhu

JMLR 2017 Online Bayesian Passive-Aggressive Learning Tianlin Shi, Jun Zhu

NeurIPS 2017 Population Matching Discrepancy and Applications in Deep Learning Jianfei Chen, Chongxuan Li, Yizhong Ru, Jun Zhu

IJCAI 2017 Semi-Supervised Max-Margin Topic Model with Manifold Posterior Regularization Wenbo Hu, Jun Zhu, Hang Su, Jingwei Zhuo, Bo Zhang

NeurIPS 2017 Structured Generative Adversarial Networks Zhijie Deng, Hao Zhang, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P Xing

NeurIPS 2017 Triple Generative Adversarial Nets Chongxuan Li, Taufik Xu, Jun Zhu, Bo Zhang

AAAI 2016 Bayesian Matrix Completion via Adaptive Relaxed Spectral Regularization Yang Song, Jun Zhu

NeurIPS 2016 Conditional Generative Moment-Matching Networks Yong Ren, Jun Zhu, Jialian Li, Yucen Luo

IJCAI 2016 Crowd Scene Understanding with Coherent Recurrent Neural Networks Hang Su, Yinpeng Dong, Jun Zhu, Haibin Ling, Bo Zhang

AAAI 2016 Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation Bei Chen, Ning Chen, Jun Zhu, Jiaming Song, Bo Zhang

ICML 2016 Diversity-Promoting Bayesian Learning of Latent Variable Models Pengtao Xie, Jun Zhu, Eric Xing

ECCV 2016 Efficient and Robust Semi-Supervised Learning over a Sparse-Regularized Graph Hang Su, Jun Zhu, Zhaozheng Yin, Yinpeng Dong, Bo Zhang

AAAI 2016 Jointly Modeling Topics and Intents with Global Order Structure Bei Chen, Jun Zhu, Nan Yang, Tian Tian, Ming Zhou, Bo Zhang

NeurIPS 2016 Kernel Bayesian Inference with Posterior Regularization Yang Song, Jun Zhu, Yong Ren

ICML 2016 Learning to Generate with Memory Chongxuan Li, Jun Zhu, Bo Zhang

CVPRW 2016 Neuron Segmentation Based on CNN with Semi-Supervised Regularization Kun Xu, Hang Su, Jun Zhu, Ji-Song Guan, Bo Zhang

AAAI 2016 Pose-Guided Human Parsing by an AND/OR Graph Using Pose-Context Features Fangting Xia, Jun Zhu, Peng Wang, Alan L. Yuille

NeurIPS 2016 Stochastic Gradient Geodesic MCMC Methods Chang Liu, Jun Zhu, Yang Song

IJCAI 2015 Adaptive Dropout Rates for Learning with Corrupted Features Jingwei Zhuo, Jun Zhu, Bo Zhang

ICML 2015 DP-Space: Bayesian Nonparametric Subspace Clustering with Small-Variance Asymptotics Yining Wang, Jun Zhu

NeurIPS 2015 Max-Margin Deep Generative Models Chongxuan Li, Jun Zhu, Tianlin Shi, Bo Zhang

NeurIPS 2015 Max-Margin Majority Voting for Learning from Crowds Tian Tian, Jun Zhu

IJCAI 2015 Modelling High-Dimensional Sequences with LSTM-RTRBM: Application to Polyphonic Music Generation Qi Lyu, Zhiyong Wu, Jun Zhu, Helen Meng

ECCV 2014 An Active Patch Model for Real World Texture and Appearance Classification Junhua Mao, Jun Zhu, Alan L. Yuille

JMLR 2014 Bayesian Inference with Posterior Regularization and Applications to Infinite Latent SVMs Jun Zhu, Ning Chen, Eric P. Xing

ICML 2014 Bayesian Max-Margin Multi-Task Learning with Data Augmentation Chengtao Li, Jun Zhu, Jianfei Chen

NeurIPS 2014 Distributed Bayesian Posterior Sampling via Moment Sharing Minjie Xu, Balaji Lakshminarayanan, Yee Whye Teh, Jun Zhu, Bo Zhang

AAAI 2014 Dropout Training for Support Vector Machines Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang

JMLR 2014 Gibbs Max-Margin Topic Models with Data Augmentation Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang

NeurIPS 2014 Learning from Weakly Supervised Data by the Expectation Loss SVM (e-SVM) Algorithm Jun Zhu, Junhua Mao, Alan L. Yuille

ICML 2014 Max-Margin Infinite Hidden Markov Models Aonan Zhang, Jun Zhu, Bo Zhang

ICML 2014 Online Bayesian Passive-Aggressive Learning Tianlin Shi, Jun Zhu

NeurIPS 2014 Robust Bayesian Max-Margin Clustering Changyou Chen, Jun Zhu, Xinhua Zhang

ICML 2014 Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models Shike Mei, Jun Zhu, Jerry Zhu

AAAI 2014 Small-Variance Asymptotics for Dirichlet Process Mixtures of SVMs Yining Wang, Jun Zhu

NeurIPS 2014 Spectral Methods for Supervised Topic Models Yining Wang, Jun Zhu

ICCV 2013 Action Recognition with Actons Jun Zhu, Baoyuan Wang, Xiaokang Yang, Wenjun Zhang, Zhuowen Tu

ICML 2013 Fast Max-Margin Matrix Factorization with Data Augmentation Minjie Xu, Jun Zhu, Bo Zhang

IJCAI 2013 Generalized Relational Topic Models with Data Augmentation Ning Chen, Jun Zhu, Fei Xia, Bo Zhang

ICML 2013 Gibbs Max-Margin Topic Models with Fast Sampling Algorithms Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang

NeurIPS 2013 Scalable Inference for Logistic-Normal Topic Models Jianfei Chen, Jun Zhu, Zi Wang, Xun Zheng, Bo Zhang

ECML-PKDD 2013 Sparse Relational Topic Models for Document Networks Aonan Zhang, Jun Zhu, Bo Zhang

WACV 2012 Learning Reconfigurable Scene Representation by Tangram Model Jun Zhu, Tianfu Wu, Song-Chun Zhu, Xiaokang Yang, Wenjun Zhang

ICML 2012 Max-Margin Nonparametric Latent Feature Models for Link Prediction Jun Zhu

JMLR 2012 MedLDA: Maximum Margin Supervised Topic Models Jun Zhu, Amr Ahmed, Eric P. Xing

NeurIPS 2012 Monte Carlo Methods for Maximum Margin Supervised Topic Models Qixia Jiang, Jun Zhu, Maosong Sun, Eric P. Xing

NeurIPS 2012 Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction Minjie Xu, Jun Zhu, Bo Zhang

NeurIPS 2011 Infinite Latent SVM for Classification and Multi-Task Learning Jun Zhu, Ning Chen, Eric P. Xing

ICML 2011 Infinite SVM: A Dirichlet Process Mixture of Large-Margin Kernel Machines Jun Zhu, Ning Chen, Eric P. Xing

UAI 2011 Sparse Topical Coding Jun Zhu, Eric P. Xing

NeurIPS 2010 Adaptive Multi-Task Lasso: With Application to eQTL Detection Seunghak Lee, Jun Zhu, Eric P. Xing

ICML 2010 Conditional Topic Random Fields Jun Zhu, Eric P. Xing

NeurIPS 2010 Efficient Relational Learning with Hidden Variable Detection Ni Lao, Jun Zhu, Liu Liu, Yandong Liu, William W. Cohen

NeurIPS 2010 Large Margin Learning of Upstream Scene Understanding Models Jun Zhu, Li-jia Li, Li Fei-fei, Eric P. Xing

NeurIPS 2010 Predictive Subspace Learning for Multi-View Data: A Large Margin Approach Ning Chen, Jun Zhu, Eric P. Xing

JMLR 2009 Maximum Entropy Discrimination Markov Networks Jun Zhu, Eric P. Xing

ICML 2009 MedLDA: Maximum Margin Supervised Topic Models for Regression and Classification Jun Zhu, Amr Ahmed, Eric P. Xing

ICML 2009 On Primal and Dual Sparsity of Markov Networks Jun Zhu, Eric P. Xing

JMLR 2008 Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen

ICML 2008 Laplace Maximum Margin Markov Networks Jun Zhu, Eric P. Xing, Bo Zhang

NeurIPS 2008 Partially Observed Maximum Entropy Discrimination Markov Networks Jun Zhu, Eric P. Xing, Bo Zhang

ICML 2007 Dynamic Hierarchical Markov Random Fields and Their Application to Web Data Extraction Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen

ICML 2005 2D Conditional Random Fields for Web Information Extraction Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, Wei-Ying Ma

IJCAI 1999 Remembering to Add: Competence-Preserving Case-Addition Policies for Case Base Maintenance Jun Zhu, Qiang Yang