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Algorithm and Hardness for Kernel Matrices in Numerical Linear Algebra and Machine Learning
Presenter
- Zhao Song
February 4, 2020
IAS
New Progress on Stochastic Variance-Reduced Methods in Machine Learning: Adaptive Restart and Distributed Optimization
Presenter
- Qihang Lin
December 12, 2017
IMA
High-throughput Data and New representations for Models and Machine Learning
Presenter
- Gus Hart
February 24, 2015
IPAM
Data-efficient kernel methods for learning differential equations and their solution operators
Presenter
- Bamdad Hosseini
October 8, 2025
IMSI
Active learning of Boltzmann samplers and potential energies with quantum mechanical accuracy
Presenter
- Pilar Cossio
April 25, 2024
IMSI
Unpacking the ingredients of atomic representations: machine learning force fields and beyond
Presenter
- Jigyasa Nigam
April 9, 2024
IMSI
Paul Grigas - Offline and Online Learning for Contextual Stochastic Optimization - IPAM at UCLA
Presenter
- Paul Grigas
March 3, 2023
IPAM
Dealing with COVID-19 in Theory and Practice: Session II: Data Science I
Presenters
- Mihaela van der Schaar
- Michael Jordan
October 29, 2020
IMSI
How to assess scientific machine learning models? Prediction errors and predictive uncertainty quantification
Presenter
- Matthias Rupp
November 21, 2019
IPAM
Deep Learning Dive into the Scanning Transmission Electron Microscopy: Materials Design, Learning Physics, and Atomic Manipulation
Presenter
- Sergei Kalinin
October 17, 2019
IPAM
Molecular design blueprints: materials and catalysts from new simulation and machine learning tools
Presenter
- Heather Kulik
October 15, 2019
IPAM