Videos

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Continuous Optimization and Applications: Graduate Course - Lecture 31 Thumbnail

Continuous Optimization and Applications: Graduate Course - Lecture 31

Presenters
  • Nathan Krislock
  • Henry Wolkowicz
July 20, 2007
SLMath
Continuous Optimization and Applications: Graduate Course - Lecture 20 Thumbnail

Continuous Optimization and Applications: Graduate Course - Lecture 20

Presenters
  • Nathan Krislock
  • Henry Wolkowicz
July 17, 2007
SLMath

Andy Rothstein - AI-Driven Event Prediction and Fault-Resilient Plasma Control on DIII-D

May 21, 2026
IPAM

Jeff Schneider - Reinforcement Learning and Bayesian Optimization for Nuclear Fusion

May 19, 2026
IPAM

Shancong Mou - Derivative-Informed Training of Neural Operators on the Fly

May 22, 2026
IPAM

Cory Hauck - Approximate entropy-based moment closures

May 19, 2026
IPAM

Michael Abdelmalik - "A Multi-Fidelity Framework for Rarefied Dynamics: Hierarchical Models, Multi-Scale Closures and Acceleration with Neural Green's Operators"

May 19, 2026
IPAM
Model-based production optimization and history matching – some (not so) recent developments Thumbnail

Model-based production optimization and history matching – some (not so) recent developments

Presenter
  • Jan Jansen
May 23, 2017
IPAM
Ruizhe Zhang - Quantum Speedups of Continuous Sampling and Optimization Problems - IPAM at UCLA Thumbnail

Ruizhe Zhang - Quantum Speedups of Continuous Sampling and Optimization Problems - IPAM at UCLA

October 6, 2023
IPAM
Anirban Chaudhuri - Multifidelity surrogates and decision-making for digital twins - IPAM at UCLA Thumbnail

Anirban Chaudhuri - Multifidelity surrogates and decision-making for digital twins - IPAM at UCLA

Presenter
  • Anirban Chaudhuri
March 26, 2026
IPAM
Constraint-Aware Self-Improving Large Language Model for Clinical Role Model Generation Thumbnail

Constraint-Aware Self-Improving Large Language Model for Clinical Role Model Generation

Presenter
  • Esmaeil Keyvanshokooh
February 3, 2026
IMSI
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning Thumbnail

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Presenter
  • Daniel Kuhn
February 26, 2020
IPAM