教育经历

  • 2014.09 - 2019.07 清华大学 博士，计算机科学与技术系，指导老师：张钹教授
  • 2017.09 - 2018.09　 博士交换生，指导老师：Max Welling 教授
  • 2010.09 - 2014.07 清华大学 本科，交叉信息研究院（姚班）

工作经历

  • 清华大学 2019.07-2021.07　博士后，指导老师：朱军教授

研究方向

机器学习，深度生成模型。详见个人主页：https://zhenxuan00.github.io/

学生要求

态度：求真务实，精益求精

能力：数学、编程能力强的同学优先

目标：具备独立研究能力，博士毕业时成为一个领域的专家

教授课程

  • 研究生课程 概率与随机算法 秋季学期
  • 研究生课程 深度生成模型：原理与应用 春季学期

科研项目

  • 国家自然科学基金面上项目 (No. 62076145) 2021.01 - 2024.12 深度生成模型的高效、收敛的学习与推断算法研究 主持
  • 中国博士后创新人才支持计划 (No. BX20190172) 2019.07 - 2021.07 贝叶斯深度学习的模型、算法及应用研究 主持
  • 清华-华为大颗粒长期合作项目 2019.09 - 2022.08 高级机器学习理论和算法研究 子课题共同负责人

学术论文

2022
EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations
Min Zhao, Fan Bao, Chongxuan Li†, Jun Zhu†
Advances in Neural Information Processing Systems (NeurIPS)
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 and Jun Zhu
Advances in Neural Information Processing Systems (NeurIPS)
Deep reinforcement learning with credit assignment for combinatorial optimization
Dong Yan, Jiayi Weng, Shiyu Huang, Chongxuan Li, Yichi Zhou, Hang Su, Jun Zhu
Pattern Recognition
Probabilistic Neural-Symbolic Models with Inductive Posterior Constraints
Ke Su, Hang Su, Chongxuan Li, Jun Zhu, Bo Zhang
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
Fast Lossless Neural Compression with Integer-Only Discrete Flows
Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu and Bo Zhang
International Conference on Machine Learning (ICML)
Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching
Cheng Lu, Kaiwen Zheng, Fan Bao, Chongxuan Li, Jianfei Chen and Jun Zhu
International Conference on Machine Learning (ICML)
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models
Fan Bao, Chongxuan Li† , Jiacheng Sun, Jun Zhu† and Bo Zhang († corresponding author)
International Conference on Machine Learning (ICML)
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† († corresponding author)
International Conference on Learning Representations (ICLR)
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models
Fan Bao, Chongxuan Li† , Jun Zhu† and Bo Zhang († corresponding author)
International Conference on Learning Representations (ICLR) (Outstanding Paper Award, acceptence rate < 0.16%)
2021
Triple Generative Adversarial Networks
Chongxuan Li, Kun Xu, Jun Zhu, Jiashuo Liu and Bo Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI, preprint)
Stability and Generalization of Bilevel Programming in Hyperparameter Optimization
Fan Bao*, Guoqiang Wu*, Chongxuan Li*, Jun Zhu and Bo Zhang (* equal contribution)
Advances in Neural Information Processing Systems (NeurIPS)
Rethinking Univariate Losses for Multi-Label Ranking: Consistency and Generalization
Guoqiang Wu*, Chongxuan Li*, Kun Xu and Jun Zhu （* equal contribution）
Advances in Neural Information Processing Systems (NeurIPS)
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† († corresponding author)
Conference on Computer Vision and Pattern Recognition (CVPR)
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu and Bo Zhang
International Conference on Machine Learning (ICML)
Implicit Normalizing Flows
Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang and Jun Zhu
International Conference on Learning Representations (ICLR) (Spotlight, acceptence rate < 5.6%)
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering
Tsung Wei Tsai, Chongxuan Li and Jun Zhu
International Conference on Learning Representations (ICLR)
2020
Understanding and Stabilizing GANs’ Training Dynamics with Control Theory
Kun Xu, Chongxuan Li, Huanshu Wei, Jun Zhu and Bo Zhang
International Conference on Machine Learning (ICML)
Learning Implicit Generative Models by Teaching Explicit Ones
Kun Xu, Chao Du, Chongxuan Li, Jun Zhu and Bo Zhang
European Conference on Machine Learning (ECML)
Efficient Learning of Generative Models via Finite-Difference Score Matching
Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon and Jun Zhu
Advances in Neural Information Processing Systems (NeurIPS)
Bi-level Score Matching for Learning Energy-based Latent Variable Models
Fan Bao*, Chongxuan Li*, Kun Xu, Hang Su, Jun Zhu and Bo Zhang (* equal contribution)
Advances in Neural Information Processing Systems (NeurIPS)
To Relieve Your Headache of Training an MRF, Take AdVIL
Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu and Bo Zhang
International Conference on Learning Representations (ICLR)
2019
Multi-objects Generation with Amortized Structural Regularization
Kun Xu, Chongxuan Li, Jun Zhu and Bo Zhang
Advances in Neural Information Processing Systems (NeurIPS)
Conditional Graphical Generative Adversarial Networks
Chongxuan Li, Jun Zhu and Bo Zhang
Journal of Software (in Chinese)
2018
Collaborative Filtering with User-Item Co-Autoregressive Models
Chao Du,Chongxuan Li, Yin Zheng, Jun Zhu and Bo Zhang
Association for the Advancement of Artificial Intelligence (AAAI)
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples
Danyang Sun, Tongzheng Ren, Chongxuan Li, Jun Zhu, and Hang Su
International Joint Conferences on Artificial Intelligence (IJCAI)
Graphical Generative Adversarial Networks
Chongxuan Li, Max Welling, Jun Zhu and Bo Zhang
Advances in Neural Information Processing Systems (NeurIPS)
Max-Margin Deep Generative Models for (Semi-)Supervised Learning
Chongxuan Li, Jun Zhu and Bo Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
2017
Population Matching Discrepancy and Applications in Deep Learning
Jianfei Chen, Chongxuan Li, Yizhong Ru and Jun Zhu
Advances in Neural Information Processing Systems (NeurIPS)
Triple Generative Adversarial Nets
Chongxuan Li, Kun Xu, Jun Zhu and Bo Zhang
Advances in Neural Information Processing Systems (NeurIPS)
2016
Towards Better Analysis of Deep Convolutional Neural Networks
Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, and Shixia Liu
IEEE VAST, TVCG track
Learning to Generate with Memory
Chongxuan Li, Jun Zhu and Bo Zhang
International Conference on Machine Learning (ICML)
2015
Max-Margin Deep Generative Models
Chongxuan Li, Jun Zhu, Tianlin Shi and Bo Zhang
Advances in Neural Information Processing Systems (NeurIPS)

荣誉奖励

  • ACM SIGAI China 新星奖 2023
  • 吴文俊优秀青年奖 2022
  • 北京市科技新星 2022
  • ICLR 杰出论文奖 2022
  • 吴文俊人工智能自然科学奖一等奖 （第五完成人）2021
  • 中国计算机学会（CCF）优秀博士学位论文奖 2019
  • 清华大学水木学者 2019
  • 中国博士后创新人才支持计划 2019
  • 微软学者（MSRA fellowship）2017
  • IEEE vizdoom 国际强化学习竞赛第二名 2017

社会兼职

  • 领域主席：ICLR 2024
  • 高级程序委员：IJCAI 2021

联系

电话：--

邮箱：chongxuanli@ruc.edu.cn

个人网页：https://zhenxuan00.github.io/

办公地址：--