Invited Speakers
William Benter Distinguished Lecture SeriesXIA Zhihong Jeff, Great Bay University, China
Tutorials:
JIAO Yuling, Wuhan University, China
Theory for deep generative learning
LEE Juho, Korea Advanced Institute of Science & Technology (KAIST), Korea
Generative modeling with diffusion models
WANG Lei, Chinese Academy of Sciences, China
A Physicists Perspective on Generative Models
Presentations:
CAO Yu, Shanghai Jiao Tong University, China
CHEN Jingrun, University of Science and Technology of China, China
Consensus-based optimization methods with adaptive momentum estimation
GAO Xuefeng, The Chinese University of Hong Kong, Hong Kong
Reward-Directed Score-Based Diffusion Models via q-Learning
HOU Junhui, The Chinese University of Hong Kong, Hong Kong
3D Scene Reconstruction and Generation
Huang Yuanfei, City University of Hong Kong, Hong Kong
Balancing Diffusion and L?vy-Based Generative Modeling: A Stochastic Thermodynamics Approach with Active Ornstein-Uhlenbeck Particles
LI Gen, The Chinese University of Hong Kong, Hong Kong
Faster Convergence and Acceleration for Diffusion-Based Generative Models
LIU Zhaoqiang, University of Electronic Science and Technology of China, China
Recent Advances in Solving Imaging Inverse Problems using Diffusion Models
MOU Chenchen, City University of Hong Kong, Hong Kong
QI Shuren, The Chinese University of Hong Kong, Hong Kong
Rethink Deep Learning with Invariance in Data Representation
TANG Rong, Hong Kong University of Science and Technology, Hong Kong
Minimax Optimal Rates for Distribution Regression
WANG Zhongjian, Nanyang Technological University, Singapore
Wasserstein bounds of flow based generative models
WANG Yuguang, Shanghai Jiao Tong University, China
Multimodal LLM for Protein Design
WEI Chaozhen, University of Electronic Science and Technology of China, China
Primal dual methods for minimizing movement schemes with general nonlinear mobility transport distances
YUAN Yancheng, Hong Kong Polytechnic University, Hong Kong
HOT: An efficient Halpern accelerating algorithm for optimal transport problems
ZENG Jia, Huawei, China
Towards Physical AI 2050
ZHANG Xiaoqun, Shanghai Jiao Tong University, China
Flow based generative models for medical image synthesis
ZHANG Zhiwen, The University of Hong Kong, Hong Kong
A Bidirectional DeepParticle Method for Efficiently Solving Low-dimensional Transport Map Problems
ZHOU Peijie, Peking University, China
Towards AI Virtual Cell Through Dynamical Generative Modeling of Single-cell Omics Data
ZHOU Kai, The Chinese University of Hong Kong(Shenzhen), China
ZHU Tong, East China Normal University, Shanghai, China
AI-Physics Dual-Driven Chemical Reaction Network Construction
ZOU Difan, The University of Hong Kong, Hong Kong
Towards understanding the representation learning of diffusion models