Videos

Start date cannot be after end date.

Boris Kramer - Structure-preserving Lift & Learn: Scientific machine learning for nonlinear conservative partial differential equations

April 17, 2026
IPAM

Solving and Learning Partial Differential Equations with Q-Exponential Processes

Presenter
  • Shiwei Lan
March 6, 2026
ICERM
Data-efficient kernel methods for learning differential equations and their solution operators Thumbnail

Data-efficient kernel methods for learning differential equations and their solution operators

Presenter
  • Bamdad Hosseini
October 8, 2025
IMSI
Constraining the outputs of ReLu neural networks Thumbnail

Constraining the outputs of ReLu neural networks

Presenter
  • Yulia Alexandr
July 21, 2025
IMSI
The mean-squared-error is not enough: Improved prediction of chaotic dynamical systems with scientific machine learning Thumbnail

The mean-squared-error is not enough: Improved prediction of chaotic dynamical systems with scientific machine learning

Presenter
  • Romit Maulik
June 13, 2025
IMSI

Recent developments in nonlinear random matrices

Presenter
  • Yizhe Zhu
May 22, 2024
ICERM
Expressing The Density Matrix as Functional Of The Density: How To Profit From Machine Learning? Thumbnail

Expressing The Density Matrix as Functional Of The Density: How To Profit From Machine Learning?

Presenter
  • Lucia Reining
March 28, 2024
IMSI
Samuel Blau - High-Throughput DFT and Monte Carlo for Reaction Networks and Machine Learning Thumbnail

Samuel Blau - High-Throughput DFT and Monte Carlo for Reaction Networks and Machine Learning

Presenter
  • Samuel Blau
May 1, 2023
IPAM
Aidan Thompson - LAMMPS simulation: physics models, machine-learning potentials, exascale computing Thumbnail

Aidan Thompson - LAMMPS simulation: physics models, machine-learning potentials, exascale computing

Presenter
  • Aidan Thompson
March 27, 2023
IPAM
Kyunghyun Cho - Lab-in-the-loop de novo antibody design - what are we missing from machine learning? Thumbnail

Kyunghyun Cho - Lab-in-the-loop de novo antibody design - what are we missing from machine learning?

Presenter
  • Kyunghyun Cho
January 25, 2023
IPAM
Mark Tuckerman - From A to B via a synthesis of rare-event sampling and machine learning Thumbnail

Mark Tuckerman - From A to B via a synthesis of rare-event sampling and machine learning

Presenter
  • Mark Tuckerman
January 24, 2023
IPAM

Robust and Scalable Learning of Gaussian Mixture Models

Presenter
  • Kisung You
December 17, 2021
ICERM