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Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling and computation under uncertainty
Presenter
- Paris Perdikaris
September 28, 2018
IPAM
Finding patterns and drawing maps in the configuration space of materials and molecules
Presenter
- Michele Ceriotti
February 23, 2015
IPAM
Jacob Miller - Synergy Between Quantum Circuits and Tensor Networks - IPAM at UCLA
Presenter
- Jacob Miller
November 8, 2023
IPAM
Jarrod McClean - The role of data, precomputation, and communication in a quantum learning landscape
Presenter
- Jarrod McClean
October 20, 2023
IPAM
Hot Topics: Shape and Structure Of Materials - Applications of convnets to microstructural description and material design
Presenter
- Daniela Ushizima
October 1, 2018
SLMath
Three principles of data science: predictability, stability, and computability
Presenter
- Bin Yu
September 14, 2016
IMA
Victor Artigues - Plasma Turbulence in TensorFlow: Reduced Models and Optimization - IPAM at UCLA
Presenter
- Victor Artigues
March 23, 2026
IPAM
Craig Plaisance - Modeling Electrocatalysis Without the Pain: Past, Present, and Future
Presenter
- Craig Plaisance
October 6, 2025
IPAM
Lars Ruthotto - Mixed-Precision Algorithms for Training Neural ODEs - IPAM at UCLA
Presenter
- Lars Ruthotto
July 14, 2025
IPAM