Chongxuan Li

ORCID

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 107

Top Venues

Publications

Ke Su, Hang Su, Chongxuan Li, Jun Zhu, Bo Zhang
Probabilistic Neural-Symbolic Models With Inductive Posterior Constraints. IEEE Trans. Neural Networks Learn. Syst. 35 (2) (2024)
Guoxing Yang, Haoyu Lu, Chongxuan Li, Guang Zhou, Haoran Wu, Zhiwu Lu
Progressive Image Synthesis from Semantics to Details with Denoising Diffusion GAN. ICASSP (2024)
Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference. ICLR (2024)
Zhengyi Wang, Yikai Wang, Yifei Chen, Chendong Xiang, Shuo Chen, Dajiang Yu, Chongxuan Li, Hang Su, Jun Zhu
CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model. CoRR (2024)
Yijing Liu, Chao Du, Tianyu Pang, Chongxuan Li, Wei Chen, Min Lin
Graph Diffusion Policy Optimization. CoRR (2024)
Jingyang Ou, Shen Nie, Kaiwen Xue, Fengqi Zhu, Jiacheng Sun, Zhenguo Li, Chongxuan Li
Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data. CoRR (2024)
Shen Nie, Hanzhong Allan Guo, Cheng Lu, Yuhao Zhou, Chenyu Zheng, Chongxuan Li
The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing. ICLR (2024)
Luxi Chen, Zhengyi Wang, Chongxuan Li, Tingting Gao, Hang Su, Jun Zhu
MicroDreamer: Zero-shot 3D Generation in ~20 Seconds by Score-based Iterative Reconstruction. CoRR (2024)
Min Zhao, Hongzhou Zhu, Chendong Xiang, Kaiwen Zheng, Chongxuan Li, Jun Zhu
Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model. CoRR (2024)
Zebin You, Xinyu Zhang, Hanzhong Guo, Jingdong Wang, Chongxuan Li
Are Image Distributions Indistinguishable to Humans Indistinguishable to Classifiers? CoRR (2024)
Chenyu Zheng, Wei Huang, Rongzhen Wang, Guoqiang Wu, Jun Zhu, Chongxuan Li
On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability. CoRR (2024)
Yong Zhong, Min Zhao, Zebin You, Xiaofeng Yu, Changwang Zhang, Chongxuan Li
PoseCrafter: One-Shot Personalized Video Synthesis Following Flexible Pose Control. CoRR (2024)
Kaiwen Xue, Yuhao Zhou, Shen Nie, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations. CoRR (2024)
Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation. NeurIPS (2023)
Shen Nie, Hanzhong Allan Guo, Cheng Lu, Yuhao Zhou, Chenyu Zheng, Chongxuan Li
The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing. CoRR (2023)
Chenyu Zheng, Guoqiang Wu, Chongxuan Li
Toward Understanding Generative Data Augmentation. NeurIPS (2023)
Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, Chongxuan Li
Gaussian Mixture Solvers for Diffusion Models. NeurIPS (2023)
Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation. CoRR (2023)
Xiangming Gu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Ye Wang
On Memorization in Diffusion Models. CoRR (2023)
Guoqiang Wu, Chongxuan Li, Yilong Yin
Towards Understanding Generalization of Macro-AUC in Multi-label Learning. CoRR (2023)
Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, Min Lin
On Evaluating Adversarial Robustness of Large Vision-Language Models. CoRR (2023)
Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference. CoRR (2023)
Fan Bao, Shen Nie, Kaiwen Xue, Yue Cao, Chongxuan Li, Hang Su, Jun Zhu
All are Worth Words: A ViT Backbone for Diffusion Models. CVPR (2023)
Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
Equivariant Energy-Guided SDE for Inverse Molecular Design. ICLR (2023)
Ximing Xing, Chuang Wang, Haitao Zhou, Zhihao Hu, Chongxuan Li, Dong Xu, Qian Yu
Inversion-by-Inversion: Exemplar-based Sketch-to-Photo Synthesis via Stochastic Differential Equations without Training. CoRR (2023)
Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu
Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning. ICML (2023)
Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shi Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, Jun Zhu
One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale. ICML (2023)
Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu
Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning. CoRR (2023)
Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu
Revisiting Discriminative vs. Generative Classifiers: Theory and Implications. ICML (2023)
Yong Zhong, Hongtao Liu, Xiaodong Liu, Fan Bao, Weiran Shen, Chongxuan Li
Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models. ICLR (2023)
Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, Chongxuan Li
Gaussian Mixture Solvers for Diffusion Models. CoRR (2023)
Yudeng Lin, Qingtian Zhang, Bin Gao, Jianshi Tang, Peng Yao, Chongxuan Li, Shiyu Huang, Zhengwu Liu, Ying Zhou, Yuyi Liu, Wenqiang Zhang, Jun Zhu, He Qian, Huaqiang Wu
Uncertainty quantification via a memristor Bayesian deep neural network for risk-sensitive reinforcement learning. Nat. Mac. Intell. 5 (7) (2023)
Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, Jun Zhu
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels. CoRR (2023)
Min Zhao, Rongzhen Wang, Fan Bao, Chongxuan Li, Jun Zhu
ControlVideo: Adding Conditional Control for One Shot Text-to-Video Editing. CoRR (2023)
Chenyu Zheng, Guoqiang Wu, Chongxuan Li
Toward Understanding Generative Data Augmentation. CoRR (2023)
Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu
Revisiting Discriminative vs. Generative Classifiers: Theory and Implications. CoRR (2023)
Guoqiang Wu, Chongxuan Li, Yilong Yin
Towards Understanding Generalization of Macro-AUC in Multi-label Learning. ICML (2023)
Yidong Ouyang, Liyan Xie, Chongxuan Li, Guang Cheng
MissDiff: Training Diffusion Models on Tabular Data with Missing Values. CoRR (2023)
Chendong Xiang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu
A Closer Look at Parameter-Efficient Tuning in Diffusion Models. CoRR (2023)
Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, Jun Zhu
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels. NeurIPS (2023)
Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, Min Lin
On Evaluating Adversarial Robustness of Large Vision-Language Models. NeurIPS (2023)
Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shi Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, Jun Zhu
One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale. CoRR (2023)
Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu
Memory Replay with Data Compression for Continual Learning. ICLR (2022)
Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models. CoRR (2022)
Yong Zhong, Hongtao Liu, Xiaodong Liu, Fan Bao, Weiran Shen, Chongxuan Li
Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models. CoRR (2022)
Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu
EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations. CoRR (2022)
Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching. ICML (2022)
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models. CoRR (2022)
Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu
EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations. NeurIPS (2022)
Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang
Fast Lossless Neural Compression with Integer-Only Discrete Flows. ICML (2022)
Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang
Fast Lossless Neural Compression with Integer-Only Discrete Flows. CoRR (2022)
Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models. CoRR (2022)
Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models. ICML (2022)
Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
Equivariant Energy-Guided SDE for Inverse Molecular Design. CoRR (2022)
Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models. ICLR (2022)
Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu
Memory Replay with Data Compression for Continual Learning. CoRR (2022)
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. CoRR (2022)
Dong Yan, Jiayi Weng, Shiyu Huang, Chongxuan Li, Yichi Zhou, Hang Su, Jun Zhu
Deep reinforcement learning with credit assignment for combinatorial optimization. Pattern Recognit. 124 (2022)
Fan Bao, Chongxuan Li, Yue Cao, Jun Zhu
All are Worth Words: a ViT Backbone for Score-based Diffusion Models. CoRR (2022)
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. NeurIPS (2022)
Chongxuan Li, Kun Xu, Jun Zhu, Jiashuo Liu, Bo Zhang
Triple Generative Adversarial Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu
Why Are Conditional Generative Models Better Than Unconditional Ones? CoRR (2022)
Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
Maximum Likelihood Training for Score-Based Diffusion ODEs by High-Order Denoising Score Matching. CoRR (2022)
Tsung Wei Tsai, Chongxuan Li, Jun Zhu
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering. ICLR (2021)
Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang
Stability and Generalization of Bilevel Programming in Hyperparameter Optimization. CoRR (2021)
Qijun Luo, Zhili Liu, Lanqing Hong, Chongxuan Li, Kuo Yang, Liyuan Wang, Fengwei Zhou, Guilin Li, Zhenguo Li, Jun Zhu
Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation. CoRR (2021)
Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu
Implicit Normalizing Flows. ICLR (2021)
Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning. CoRR (2021)
Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning. CVPR (2021)
Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models. ICML (2021)
Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu
Implicit Normalizing Flows. CoRR (2021)
Tsung Wei Tsai, Chongxuan Li, Jun Zhu
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering. CoRR (2021)
Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang
Stability and Generalization of Bilevel Programming in Hyperparameter Optimization. NeurIPS (2021)
Guoqiang Wu, Chongxuan Li, Kun Xu, Jun Zhu
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization. CoRR (2021)
Guoqiang Wu, Chongxuan Li, Kun Xu, Jun Zhu
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization. NeurIPS (2021)
Fan Bao, Chongxuan Li, Taufik Xu, Hang Su, Jun Zhu, Bo Zhang
Bi-level Score Matching for Learning Energy-based Latent Variable Models. NeurIPS (2020)
Fan Bao, Chongxuan Li, Kun Xu, Hang Su, Jun Zhu, Bo Zhang
Bi-level Score Matching for Learning Energy-based Latent Variable Models. CoRR (2020)
Kun Xu, Chao Du, Chongxuan Li, Jun Zhu, Bo Zhang
Learning Implicit Generative Models by Teaching Density Estimators. ECML/PKDD (2) (2020)
Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu
Efficient Learning of Generative Models via Finite-Difference Score Matching. CoRR (2020)
Tianyu Pang, Taufik Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu
Efficient Learning of Generative Models via Finite-Difference Score Matching. NeurIPS (2020)
Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang
To Relieve Your Headache of Training an MRF, Take AdVIL. ICLR (2020)
Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models. CoRR (2020)
Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang
Understanding and Stabilizing GANs' Training Dynamics Using Control Theory. ICML (2020)
Chongxuan Li, Kun Xu, Jiashuo Liu, Jun Zhu, Bo Zhang
Triple Generative Adversarial Networks. CoRR (2019)
Taufik Xu, Chongxuan Li, Jun Zhu, Bo Zhang
Multi-objects Generation with Amortized Structural Regularization. NeurIPS (2019)
Tsung Wei Tsai, Chongxuan Li, Jun Zhu
L: Deep Self-Semi-Supervised Learning for Image Recognition. CoRR (2019)
Kun Xu, Chongxuan Li, Huanshu Wei, Jun Zhu, Bo Zhang
Understanding and Stabilizing GANs' Training Dynamics with Control Theory. CoRR (2019)
Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang
Adversarial Variational Inference and Learning in Markov Random Fields. CoRR (2019)
Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang
Multi-objects Generation with Amortized Structural Regularization. CoRR (2019)
Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang
Graphical Generative Adversarial Networks. CoRR (2018)
Danyang Sun, Tongzheng Ren, Chongxuan Li, Hang Su, Jun Zhu
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. IJCAI (2018)
Chongxuan Li, Jun Zhu, Bo Zhang
Max-Margin Deep Generative Models for (Semi-)Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. 40 (11) (2018)
Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang
Graphical Generative Adversarial Networks. NeurIPS (2018)
Chao Du, Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang
Learning Implicit Generative Models by Teaching Explicit Ones. CoRR (2018)
Chao Du, Chongxuan Li, Yin Zheng, Jun Zhu, Bo Zhang
Collaborative Filtering With User-Item Co-Autoregressive Models. AAAI (2018)
Chongxuan Li, Kun Xu, Jun Zhu, Bo Zhang
Triple Generative Adversarial Nets. CoRR (2017)
Danyang Sun, Tongzheng Ren, Chongxuan Li, Jun Zhu, Hang Su
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. CoRR (2017)
Chongxuan Li, Taufik Xu, Jun Zhu, Bo Zhang
Triple Generative Adversarial Nets. NIPS (2017)
Jianfei Chen, Chongxuan Li, Yizhong Ru, Jun Zhu
Population Matching Discrepancy and Applications in Deep Learning. NIPS (2017)
Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu
Towards Better Analysis of Deep Convolutional Neural Networks. IEEE Trans. Vis. Comput. Graph. 23 (1) (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Chongxuan Li