Videos

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Can NNs Learn Generalizable (Geometric) Algorithms

Presenter
  • Yusu Wang
May 19, 2026
ICERM

Alexander Velberg - Data-driven discovery of sub-grid models for collisionless magnetic reconnection

April 18, 2026
IPAM

Guannan Zhang - Generative diffusion models for learning stochastic flow maps in particle-based kinetic simulation

April 17, 2026
IPAM

Benjamin Sanderse - Structure-preserving SciML for discovering ODEs and SDEs in fluid flows

April 17, 2026
IPAM

Ammar Hakim - BEACONS and BEACONS-FM: Lighting a Path to Modular, Composable, Formally Verified Fusion Foundation Models

April 17, 2026
IPAM

End-to-End Training of High-Dimensional Optimal Control with Implicit Hamiltonians via Jacobian-Free Backpropagation

Presenter
  • Deepanshu Verma
April 16, 2026
ICERM

Diego Del-Castillo-Negrete - Generative Artificial Intelligence methods for turbulence and kinetic computations

April 16, 2026
IPAM

Jiequn Han - Learning Evolution Operators Across PDE Systems: Meta-Learning and Test-Time Generalization

April 15, 2026
IPAM

Peter Benner - Discovery and Model Reduction of Hamiltonian Systems

April 15, 2026
IPAM

Li Wang - Suppressing Plasma Instability Through Constrained Optimization

April 14, 2026
IPAM
Victor Artigues - Plasma Turbulence in TensorFlow: Reduced Models and Optimization - IPAM at UCLA Thumbnail

Victor Artigues - Plasma Turbulence in TensorFlow: Reduced Models and Optimization - IPAM at UCLA

Presenter
  • Victor Artigues
March 23, 2026
IPAM
Andrew Christlieb - An introduction to Scientific Machine Learning - IPAM at UCLA Thumbnail

Andrew Christlieb - An introduction to Scientific Machine Learning - IPAM at UCLA

Presenter
  • Andrew Christlieb
March 13, 2026
IPAM