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Combining Stochastic Parameterized Reduced Order Models with Machine Learning for Data Assimilation and Uncertainty Quantification with Partial Observations
Presenter
- Nan Chen
October 31, 2022
IMSI
Efficient Tensor Representation for Deep Learning with TensorLy and PyTorch
Presenter
- Jean Kossaifi
May 19, 2021
IPAM
FedCBO: Reaching Group Consensus in Clustered Federated Learning and Robustness to Backdoor Adversarial Attacks.
Presenter
- Nicolas Garcia Trillos
May 10, 2024
ICERM
Wasserstein Information Geometry for Learning from Data (Part 2/2)
Presenter
- Guido Montufar
March 14, 2019
IPAM
Wasserstein Information Geometry for Learning from Data (Part 1/2)
Presenter
- Guido Montufar
March 14, 2019
IPAM
Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling and computation under uncertainty
Presenter
- Paris Perdikaris
September 28, 2018
IPAM
Scalable algorithms for optimal experimental design for large-scale Bayesian inverse problems governed by complex models
Presenter
- Omar Ghattas
October 18, 2018
IPAM
Scalable algorithms for optimal training data for Bayesian inference of large scale models
Presenter
- Omar Ghattas
September 27, 2018
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
Computing Lusztig's q-weight multiplicities beyond type A
Presenter
- Cristian Lenart
November 10, 2025
ICERM
Designing protein models with machine learning and experimental data
Presenter
- Klara Bonneau
April 26, 2024
IMSI