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Wei Zhu - Structure-preserving machine learning and data-driven structure discovery - IPAM at UCLA
Presenter
- Wei Zhu
July 18, 2025
IPAM
Markos Katsoulakis - Hamilton-Jacobi Equations, Mean-Field Games, and Optimal Control for Robust ML
Presenter
- Markos Katsoulakis
July 17, 2025
IPAM
Tingwei Meng - Bayesian sampler for inverse problems of a stochastic process by leveraging HJ PDEs
Presenter
- Tingwei Meng
July 17, 2025
IPAM
Zecheng Zhang - Deep Operator Learning Approximation and Distributed Applications - IPAM at UCLA
Presenter
- Zecheng Zhang
July 16, 2025
IPAM
Nisha Chandramoorthy - Toward physical generative modeling - IPAM at UCLA
Presenter
- Nisha Chandramoorthy
July 16, 2025
IPAM
Guang Lin - Scalable algorithms for Bayesian deep learning via stochastic gradient Monte Carlo
Presenter
- Guang Lin
July 16, 2025
IPAM
Jiajia Yu - Learning and Inference in Mean-Field Games - IPAM at UCLA
Presenter
- Jiajia Yu
July 16, 2025
IPAM
Rongjie Lai - Unsupervised In-context Operator Learning for Mean Field Games - IPAM at UCLA
Presenter
- Rongjie Lai
July 15, 2025
IPAM
Benjamin Zhang - Probabilistic operator learning: generative modeling and uncertainty quantification
Presenter
- Benjamin Zhang
July 15, 2025
IPAM
Siting Liu - Score-Based Generative Models through the Lens of Wasserstein Proximal Operators
Presenter
- Siting Liu
July 15, 2025
IPAM
Alex Cloninger - Linearized Optimal Transport to Predict Evolution of Stochastic Particle Systems
Presenter
- Alex Cloninger
July 15, 2025
IPAM
Stan Osher - A Characteristic-Based Deep Learning Framework for Hamilton–Jacobi Equations with Application to Optimal Transport
Presenter
- Stanley Osher
July 14, 2025
IPAM