Max-Margin Deep Generative Models. - Chongxuan Li; Jun Zhu 001; Tianlin Shi; Bo Zhang 010 (NIPS, 2015)

Learning to Generate with Memory. - Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (ICML, 2016)

Collaborative Filtering with User-Item Co-Autoregressive Models. - Chao Du; Chongxuan Li; Yin Zheng; Jun Zhu 001; Cailiang Liu; Hanning Zhou; Bo Zhang 010 (CoRR, 2016)

Population Matching Discrepancy and Applications in Deep Learning. - Jianfei Chen 001; Chongxuan Li; Yizhong Ru; Jun Zhu 001 (NIPS, 2017)

Triple Generative Adversarial Nets. - Chongxuan Li; Taufik Xu; Jun Zhu 001; Bo Zhang 010 (NIPS, 2017)

Triple Generative Adversarial Nets. - Chongxuan Li; Kun Xu 004; Jun Zhu 001; Bo Zhang 010 (CoRR, 2017)

Towards Better Analysis of Deep Convolutional Neural Networks. - Mengchen Liu; Jiaxin Shi; Zhen Li 044; Chongxuan Li; Jun Zhu 001; Shixia Liu (IEEE Trans. Vis. Comput. Graph., 2017)

Collaborative Filtering With User-Item Co-Autoregressive Models. - Chao Du; Chongxuan Li; Yin Zheng; Jun Zhu 001; Bo Zhang 010 (AAAI, 2018)

Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. - Danyang Sun; Tongzheng Ren; Chongxuan Li; Hang Su 006; Jun Zhu 001 (IJCAI, 2018)

Graphical Generative Adversarial Networks. - Chongxuan Li; Max Welling; Jun Zhu 001; Bo Zhang 010 (NeurIPS, 2018)

Learning Implicit Generative Models by Teaching Explicit Ones. - Chao Du; Kun Xu 004; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (CoRR, 2018)

Max-Margin Deep Generative Models for (Semi-)Supervised Learning. - Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

Multi-objects Generation with Amortized Structural Regularization. - Taufik Xu; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (NeurIPS, 2019)

Adversarial Variational Inference and Learning in Markov Random Fields. - Chongxuan Li; Chao Du; Kun Xu 004; Max Welling; Jun Zhu 001; Bo Zhang 010 (CoRR, 2019)

DS3L: Deep Self-Semi-Supervised Learning for Image Recognition. - Tsung Wei Tsai; Chongxuan Li; Jun Zhu 001 (CoRR, 2019)

Multi-objects Generation with Amortized Structural Regularization. - Kun Xu 004; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (CoRR, 2019)

Understanding and Stabilizing GANs' Training Dynamics with Control Theory. - Kun Xu 004; Chongxuan Li; Huanshu Wei; Jun Zhu 001; Bo Zhang 010 (CoRR, 2019)

To Relieve Your Headache of Training an MRF, Take AdVIL. - Chongxuan Li; Chao Du; Kun Xu 004; Max Welling; Jun Zhu 001; Bo Zhang 010 (ICLR, 2020)

Understanding and Stabilizing GANs' Training Dynamics Using Control Theory. - Kun Xu 004; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (ICML, 2020)

Bi-level Score Matching for Learning Energy-based Latent Variable Models. - Fan Bao; Chongxuan Li; Taufik Xu; Hang Su 006; Jun Zhu 001; Bo Zhang 010 (NeurIPS, 2020)

Efficient Learning of Generative Models via Finite-Difference Score Matching. - Tianyu Pang; Taufik Xu; Chongxuan Li; Yang Song 011; Stefano Ermon; Jun Zhu 001 (NeurIPS, 2020)

Learning Implicit Generative Models by Teaching Density Estimators. - Kun Xu 004; Chao Du; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (ECML/PKDD (2), 2020)

Efficient Learning of Generative Models via Finite-Difference Score Matching. - Tianyu Pang; Kun Xu 004; Chongxuan Li; Yang Song 011; Stefano Ermon; Jun Zhu 001 (CoRR, 2020)

Bi-level Score Matching for Learning Energy-based Latent Variable Models. - Fan Bao; Chongxuan Li; Kun Xu 004; Hang Su 006; Jun Zhu 001; Bo Zhang 010 (CoRR, 2020)

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 001 (CVPR, 2021)

Implicit Normalizing Flows. - Cheng Lu 011; Jianfei Chen 001; Chongxuan Li; Qiuhao Wang; Jun Zhu 001 (ICLR, 2021)

MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering. - Tsung Wei Tsai; Chongxuan Li; Jun Zhu 001 (ICLR, 2021)

Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models. - Fan Bao; Kun Xu 004; Chongxuan Li; Lanqing Hong; Jun Zhu 001; Bo Zhang 010 (ICML, 2021)

Stability and Generalization of Bilevel Programming in Hyperparameter Optimization. - Fan Bao; Guoqiang Wu; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (NeurIPS, 2021)

Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization. - Guoqiang Wu; Chongxuan Li; Kun Xu 004; Jun Zhu 001 (NeurIPS, 2021)

Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation. - Qijun Luo; Zhili Liu; Lanqing Hong; Chongxuan Li; Kuo Yang; Liyuan Wang; Fengwei Zhou; Guilin Li; Zhenguo Li; Jun Zhu 001 (CoRR, 2021)

Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models. - Fan Bao; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (ICLR, 2022)

Memory Replay with Data Compression for Continual Learning. - Liyuan Wang; Xingxing Zhang 001; Kuo Yang; Longhui Yu; Chongxuan Li; Lanqing Hong; Shifeng Zhang; Zhenguo Li; Yi Zhong; Jun Zhu 001 (ICLR, 2022)

Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models. - Fan Bao; Chongxuan Li; Jiacheng Sun; Jun Zhu 001; Bo Zhang 010 (ICML, 2022)

Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching. - Cheng Lu 011; Kaiwen Zheng; Fan Bao; Jianfei Chen 001; Chongxuan Li; Jun Zhu 001 (ICML, 2022)

Fast Lossless Neural Compression with Integer-Only Discrete Flows. - Siyu Wang; Jianfei Chen 001; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (ICML, 2022)

EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations. - Min Zhao 013; Fan Bao; Chongxuan Li; Jun Zhu 001 (NeurIPS, 2022)

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. - Cheng Lu 011; Yuhao Zhou; Fan Bao; Jianfei Chen 001; Chongxuan Li; Jun Zhu 001 (NeurIPS, 2022)

All are Worth Words: a ViT Backbone for Score-based Diffusion Models. - Fan Bao; Chongxuan Li; Yue Cao; Jun Zhu 001 (CoRR, 2022)

Why Are Conditional Generative Models Better Than Unconditional Ones? - Fan Bao; Chongxuan Li; Jiacheng Sun; Jun Zhu 001 (CoRR, 2022)

Triple Generative Adversarial Networks. - Chongxuan Li; Kun Xu 004; Jun Zhu 001; Jiashuo Liu; Bo Zhang 010 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Deep reinforcement learning with credit assignment for combinatorial optimization. - Dong Yan; Jiayi Weng; Shiyu Huang 001; Chongxuan Li; Yichi Zhou; Hang Su 006; Jun Zhu 001 (Pattern Recognit., 2022)

All are Worth Words: A ViT Backbone for Diffusion Models. - Fan Bao; Shen Nie; Kaiwen Xue; Yue Cao; Chongxuan Li; Hang Su 006; Jun Zhu 001 (CVPR, 2023)

Equivariant Energy-Guided SDE for Inverse Molecular Design. - Fan Bao; Min Zhao 013; Zhongkai Hao; Peiyao Li; Chongxuan Li; Jun Zhu 001 (ICLR, 2023)

Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models. - Yong Zhong; Hongtao Liu; Xiaodong Liu; Fan Bao; Weiran Shen; Chongxuan Li (ICLR, 2023)

Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning. - Cheng Lu 011; Huayu Chen; Jianfei Chen 001; Hang Su 006; Chongxuan Li; Jun Zhu 001 (ICML, 2023)

One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale. - Fan Bao; Shen Nie; Kaiwen Xue; Chongxuan Li; Shi Pu 002; Yaole Wang; Gang Yue; Yue Cao; Hang Su 006; Jun Zhu 001 (ICML, 2023)

Towards Understanding Generalization of Macro-AUC in Multi-label Learning. - Guoqiang Wu; Chongxuan Li; Yilong Yin (ICML, 2023)

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

Gaussian Mixture Solvers for Diffusion Models. - Hanzhong Guo; Cheng Lu 011; Fan Bao; Tianyu Pang; Shuicheng Yan; Chao Du; Chongxuan Li (NeurIPS, 2023)

ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation. - Zhengyi Wang; Cheng Lu 011; Yikai Wang 001; Fan Bao; Chongxuan Li; Hang Su 006; Jun Zhu 001 (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 (NeurIPS, 2023)

On Evaluating Adversarial Robustness of Large Vision-Language Models. - Yunqing Zhao; Tianyu Pang; Chao Du; Xiao Yang; Chongxuan Li; Ngai-Man Cheung; Min Lin (NeurIPS, 2023)

Toward Understanding Generative Data Augmentation. - Chenyu Zheng; Guoqiang Wu; Chongxuan Li (NeurIPS, 2023)

Revisiting Discriminative vs. Generative Classifiers: Theory and Implications. - Chenyu Zheng; Guoqiang Wu; Fan Bao; Yue Cao; Chongxuan Li; Jun Zhu 001 (CoRR, 2023)

Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels. - Zebin You; Yong Zhong; Fan Bao; Jiacheng Sun; Chongxuan Li; Jun Zhu 001 (CoRR, 2023)

A Closer Look at Parameter-Efficient Tuning in Diffusion Models. - Chendong Xiang; Fan Bao; Chongxuan Li; Hang Su 006; Jun Zhu 001 (CoRR, 2023)

ControlVideo: Adding Conditional Control for One Shot Text-to-Video Editing. - Min Zhao 013; Rongzhen Wang; Fan Bao; Chongxuan Li; Jun Zhu 001 (CoRR, 2023)

MissDiff: Training Diffusion Models on Tabular Data with Missing Values. - Yidong Ouyang; Liyan Xie; Chongxuan Li; Guang Cheng 003 (CoRR, 2023)

Inversion-by-Inversion: Exemplar-based Sketch-to-Photo Synthesis via Stochastic Differential Equations without Training. - Ximing Xing; Chuang Wang 008; Haitao Zhou; Zhihao Hu; Chongxuan Li; Dong Xu 001; Qian Yu (CoRR, 2023)

Uncertainty quantification via a memristor Bayesian deep neural network for risk-sensitive reinforcement learning. - Yudeng Lin; Qingtian Zhang; Bin Gao 006; Jianshi Tang; Peng Yao; Chongxuan Li; Shiyu Huang 001; Zhengwu Liu; Ying Zhou; Yuyi Liu; Wenqiang Zhang; Jun Zhu 001; et al. (Nat. Mac. Intell., 2023)

HierAffinity: Predicting Protein-Ligand Binding Affinity With Hierarchical Modeling. - Yang Zhang 094; Zhewei Wei; Wenbing Huang 001; Chongxuan Li (DASFAA (7), 2024)

TransPocket: Structural and Geometric Transformer for Ligand Binding Site Detection. - Yang Zhang 094; Zhewei Wei; Wenbing Huang 001; Chongxuan Li (DASFAA (7), 2024)

CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model. - Zhengyi Wang; Yikai Wang 001; Yifei Chen; Chendong Xiang; Shuo Chen; Dajiang Yu; Chongxuan Li; Hang Su 006; Jun Zhu 001 (ECCV (31), 2024)

Solving Inverse Problem with Unspecified Forward Operator Using Diffusion Models. - Jialing Zhang; Chongxuan Li; Dequan Wang (ECCV Workshops (9), 2024)

Lost in Translation: Latent Concept Misalignment in Text-to-Image Diffusion Models. - Juntu Zhao; Junyu Deng; Yixin Ye; Chongxuan Li; Zhijie Deng; Dequan Wang (ECCV (69), 2024)

PoseCrafter: One-Shot Personalized Video Synthesis Following Flexible Pose Control. - Yong Zhong; Min Zhao 013; Zebin You; Xiaofeng Yu; Changwang Zhang; Chongxuan Li (ECCV (44), 2024)

Progressive Image Synthesis from Semantics to Details with Denoising Diffusion GAN. - Guoxing Yang; Haoyu Lu; Chongxuan Li; Guang Zhou; Haoran Wu; Zhiwu Lu 001 (ICASSP, 2024)

BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference. - Siqi Kou; Lei Gan; Dequan Wang; Chongxuan Li; Zhijie Deng (ICLR, 2024)

The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing. - Shen Nie; Hanzhong Allan Guo; Cheng Lu 011; Yuhao Zhou; Chenyu Zheng; Chongxuan Li (ICLR, 2024)

EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction. - Yang Zhang 094; Zhewei Wei; Ye Yuan 001; Chongxuan Li; Wenbing Huang 001 (ICML, 2024)

Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations. - Kaiwen Xue; Yuhao Zhou; Shen Nie; Xu Min; Xiaolu Zhang; Jun Zhou 011; Chongxuan Li (ICML, 2024)

Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model. - Min Zhao 013; Hongzhou Zhu; Chendong Xiang; Kaiwen Zheng; Chongxuan Li; Jun Zhu 001 (NeurIPS, 2024)

Graph Diffusion Policy Optimization. - Yijing Liu; Chao Du; Tianyu Pang; Chongxuan Li; Min Lin; Wei Chen 001 (NeurIPS, 2024)

Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization. - Rongzhen Wang; Chenyu Zheng; Guoqiang Wu; Xu Min; Xiaolu Zhang; Jun Zhou; Chongxuan Li (NeurIPS, 2024)

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

MicroDreamer: Zero-shot 3D Generation in 20 Seconds by Score-based Iterative Reconstruction. - Luxi Chen; Zhengyi Wang; Chongxuan Li; Tingting Gao; Hang Su 006; Jun Zhu 001 (CoRR, 2024)

Are Image Distributions Indistinguishable to Humans Indistinguishable to Classifiers? - Zebin You; Xinyu Zhang 017; Hanzhong Guo; Jingdong Wang 001; Chongxuan Li (CoRR, 2024)

Real-time Identity Defenses against Malicious Personalization of Diffusion Models. - Hanzhong Guo; Shen Nie; Chao Du; Tianyu Pang; Hao Sun; Chongxuan Li (CoRR, 2024)

Probabilistic Neural-Symbolic Models With Inductive Posterior Constraints. - Ke Su; Hang Su 006; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Animate and Sound an Image. - Xihua Wang; Ruihua Song; Chongxuan Li; Xin Cheng 008; Boyuan Li; Yihan Wu; Yuyue Wang 003; Hongteng Xu; Yunfeng Wang (CVPR, 2025)

Are Images Indistinguishable to Humans Also Indistinguishable to Classifiers? - Zebin You; Xinyu Zhang 017; Hanzhong Guo; Jingdong Wang 001; Chongxuan Li (CVPR, 2025)

Improving Long-Text Alignment for Text-to-Image Diffusion Models. - Luping Liu; Chao Du; Tianyu Pang; Zehan Wang 001; Chongxuan Li; Dong Xu (ICLR, 2025)

Scaling up Masked Diffusion Models on Text. - Shen Nie; Fengqi Zhu; Chao Du; Tianyu Pang; Qian Liu 012; Guangtao Zeng; Min Lin; Chongxuan Li (ICLR, 2025)

Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data. - Jingyang Ou; Shen Nie; Kaiwen Xue; Fengqi Zhu; Jiacheng Sun; Zhenguo Li; Chongxuan Li (ICLR, 2025)

ControlVideo: conditional control for one-shot text-driven video editing and beyond. - Min Zhao 013; Rongzhen Wang; Fan Bao; Chongxuan Li; Jun Zhu 001 (Sci. China Inf. Sci., 2025)

On Memorization in Diffusion Models. - Xiangming Gu; Chao Du; Tianyu Pang; Chongxuan Li; Min Lin; Ye Wang 007 (Trans. Mach. Learn. Res., 2025)

Large Language Diffusion Models. - Shen Nie; Fengqi Zhu; Zebin You; Xiaolu Zhang; Jingyang Ou; Jun Hu; Jun Zhou 011; Yankai Lin; Ji-Rong Wen; Chongxuan Li (CoRR, 2025)

A Theory for Conditional Generative Modeling on Multiple Data Sources. - Rongzhen Wang; Yan Zhang; Chenyu Zheng; Chongxuan Li; Guoqiang Wu (CoRR, 2025)

RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers. - Min Zhao 013; Guande He; Yixiao Chen; Hongzhou Zhu; Chongxuan Li; Jun Zhu 001 (CoRR, 2025)

Effective and Efficient Masked Image Generation Models. - Zebin You; Jingyang Ou; Xiaolu Zhang; Jun Hu; Jun Zhou 011; Chongxuan Li (CoRR, 2025)

FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View Synthesis. - Luxi Chen; Zihan Zhou; Min Zhao; Yikai Wang; Ge Zhang 009; Wenhao Huang 001; Hao Sun 002; Ji-Rong Wen; Chongxuan Li (CoRR, 2025)

Concat-ID: Towards Universal Identity-Preserving Video Synthesis. - Yong Zhong; Zhuoyi Yang; Jiayan Teng; Xiaotao Gu; Chongxuan Li (CoRR, 2025)

Scaling Diffusion Transformers Efficiently via μP. - Chenyu Zheng; Xinyu Zhang; Rongzhen Wang; Wei Huang; Zhi Tian; Weilin Huang; Jun Zhu; Chongxuan Li (CoRR, 2025)

LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning. - Zebin You; Shen Nie; Xiaolu Zhang; Jun Hu; Jun Zhou 011; Zhiwu Lu 001; Ji-Rong Wen; Chongxuan Li (CoRR, 2025)

LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models. - Fengqi Zhu; Rongzhen Wang; Shen Nie; Xiaolu Zhang; Chunwei Wu; Jun Hu; Jun Zhou 011; Jianfei Chen; Yankai Lin; Ji-Rong Wen; Chongxuan Li (CoRR, 2025)

Reinforcing General Reasoning without Verifiers. - Xiangxin Zhou; Zichen Liu; Anya Sims; Haonan Wang; Tianyu Pang; Chongxuan Li; Liang Wang; Min Lin; Chao Du (CoRR, 2025)

A Survey on Latent Reasoning. - Ruijie Zhu 003; Tianhao Peng; Tianhao Cheng; Xingwei Qu; Jinfa Huang; Dawei Zhu; Hao Wang; Kaiwen Xue; Xuanliang Zhang; Yong Shan; Tianle Cai; Taylor Kergan; et al. (CoRR, 2025)

DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models. - Cheng Lu 011; Yuhao Zhou; Fan Bao; Jianfei Chen 001; Chongxuan Li; Jun Zhu 001 (Mach. Intell. Res., 2025)