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Fuqun Han - Regularized Wasserstein Proximal Algorithms for Nonsmooth Sampling Problems
Presenter
- Fuqun Han
July 23, 2025
IPAM
Tingwei Meng - Bayesian sampler for inverse problems of a stochastic process by leveraging HJ PDEs
Presenter
- Tingwei Meng
July 17, 2025
IPAM
Benjamin Zhang - Probabilistic operator learning: generative modeling and uncertainty quantification
Presenter
- Benjamin Zhang
July 15, 2025
IPAM
Lars Ruthotto - Mixed-Precision Algorithms for Training Neural ODEs - IPAM at UCLA
Presenter
- Lars Ruthotto
July 14, 2025
IPAM
Towards prediction uncertainty for computational physics-based models, agent-based models, and machine learning models
Presenter
- Dave Higdon
May 19, 2025
IMSI
Exploiting linear models for transferability and long-range interactions
Presenter
- Julien Lam
April 11, 2024
IMSI
Overview of classical ML: unsupervised learning and regularized regression
Presenter
- Luca Ghiringhelli
March 11, 2024
IMSI
Randomization, Neutrality, and Fairness: Characterizing General Top Trading Cycles Mechanisms
Presenter
- Bettina Klaus
October 23, 2023
SLMath
Extending Generalization Theory to Address Phenomena in Contemporary Machine Learning
Presenter
- Shay Moran
October 17, 2023
IAS
Bin Yu - Interpreting Deep Neural Networks towards Trustworthiness - IPAM at UCLA
Presenter
- Bin Yu
January 9, 2023
IPAM
Effect of Dependence on the Convergence of Empirical Wasserstein Distance
Presenter
- Nabarun Deb
May 18, 2022
IMSI
