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Machine-learning for materials and physics discovery through symbolic regression and kernel methods
Presenter
- Richard Hennig
September 26, 2019
IPAM
Intelligent learning: similarity control and knowledge transfer
Presenter
- Vladimir Vapnik
March 30, 2015
IAS
Building a Gaussian Process Statistical and Quantitative Learning Framework for Scientific Applications
Presenter
- Xiaoye Li
September 13, 2025
ICERM
A Neural Network Approach to Learning Steady States and Their Stability of Parametric Dynamical Systems
Presenter
- Xiaochuan Tian
January 9, 2025
ICERM
Yihui Quek - Signal and noise: learning with random quantum circuits and other agents of chaos
Presenter
- Yihui Quek
October 16, 2023
IPAM
Paul Grigas - Offline and Online Learning for Contextual Stochastic Optimization - IPAM at UCLA
Presenter
- Paul Grigas
March 3, 2023
IPAM
Ellen Zhoung - Machine learning for determining protein structure and dynamics from cryo-EM images
Presenter
- Ellen Zhong
November 14, 2022
IPAM
Integrating Artificial Intelligence / Machine Learning with Data Assimilation - towards the initialization of subseasonal-to-seasonal (S2S) prediction
Presenter
- Steve Penny
August 23, 2021
ICERM
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis
Presenter
- Rose Yu
May 19, 2021
IPAM
Multi-scale modeling of materials revisited: Accelerated computing and machine learning
Presenter
- Kaushik Bhattacharya
February 15, 2021
IMSI
Iterative adaptive learning for parameter and population inference
Presenter
- Richard O'Shaughnessy
November 20, 2020
ICERM
Regularity theory and uniform convergence in the large data limit of graph Laplacian eigenvectors on random data clouds
Presenter
- Nicolas Garcia Trillos
May 7, 2020
SLMath