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Invited Speakers

• Stanley Osher, UCLA
  In-Context Operator Learning with Data Prompts for Differential Equation Problems
• Lincoln Lu, USC
  Probabilistic Method for Complex Graph
• Yifan Chen, NYU
  Design of gradient flows for sampling probability distributions 
• Qi Feng, FSU
  Variational Ricci curvature Langevin dynamics: entropy dissipation and its inverse problem
• Guosheng Fu, Notre Dame
  Finite elements meet optimal transport on a Schrodinger bridge
• Shu Liu, UCLA
  A first-order computational algorithm for reaction-diffusion type equations via primal-dual hybrid gradient method
• Yiwei Wang, UC Riverside
  Energetic variational discretizations of complex fluid models
• Xianjin Yang, Caltech
  Inferring strategies and environments from observed populations for mean field games by Gaussian processes
• Bohan Zhou, UCSB
  Efficient and Exact Multimarginal Optimal Transport with Pairwise Costs 
• Mo Zhou, UCLA
  Advancing Stochastic Optimal Control: An Actor-Critic Framework
• Jia-jie Zhu, WIAS Berlin
  Robust Learning under Distribution Shift: Kernel Methods and Gradient Flow Force-Balance
• Yuan Gao, Purdue University
  Convex optimization for measures: Transition path and Mean field game for jump processes 
• Xinzhe Zuo, UCLA
• Haonan Zhang, USC
• Siming He, USC
• Jaiqi Leng, University of Maryland
• Wuchen Li, USC
• Hong Wang, USC