Invited Speakers

William Benter Distinguished Lecture
XIA Zhihong Jeff, Great Bay University, China
    Efficient Machine Learning Algorithms Inspired by Pure Math

Distinguished Lecture
HUANG Jian, The Hong Kong Polytechnic University
    Large Model-Powered Statistical Analysis

Tutorials: (Day 1)
JIAO Yuling, Wuhan University, China
    Theory for deep generative learning (Part 1 & Part 2)
LEE Juho, Korea Advanced Institute of Science & Technology (KAIST), Korea
    Generative modeling with diffusion models (Part 1 & Part 2)
WANG Lei, Chinese Academy of Sciences, China
    A Physicists Perspective on Generative Models (Part 1 & Part 2)

Presentations: (Day 2 & 3)
CAO Yu, Shanghai Jiao Tong University, China
    Exploring the Crossroads of Machine Learning and Quantum Dynamics
CHEN Jingrun, University of Science and Technology of China, China
    Consensus-based optimization methods with adaptive momentum estimation
GAO Weiguo, Fudan University, China
    Evolution of Discriminator and Generator Gradients in GAN Training: From Fitting to Collapse
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
    Advancing Spatial Intelligence from 3D/4D Representation and Learning Process
Huang Yuanfei, City University of Hong Kong, Hong Kong
    Balancing Diffusion and Levy-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
    On Well-posedness of Mean Field Game Master Equations: A Unified Approach
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
     QCD matter exploration meets Generative AI
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