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Establishing trust in decisions made from data: Physics-informed machine-learning models with computable generalization bounds
Presenter
- Benjamin Peherstorfer
March 2, 2022
IMSI
A three-pronged approach to using machine learning in knot theory
Presenter
- Mark Hughes
May 24, 2023
ICERM
Multiscale analysis of accelerated gradient methods in machine learning
Presenter
- Mohammad Farazmand
October 28, 2019
IPAM
Learning dynamics with dynamical distances: From diffusion maps to commute maps and coherence
Presenter
- Ralf Banisch
December 5, 2016
IPAM
Momentum in Stochastic Gradient Descent and Deep Neural Nets
Presenter
- Bao Wang
January 29, 2020
IPAM
Combinatorial Invariance: a Case Study of Pure Math / Machine Learning Interaction
Presenter
- Geordie Williamson
March 28, 2022
IAS
Geordie Williamson - What can the working mathematician expect from deep learning? - IPAM at UCLA
Presenter
- Geordie Williamson
February 13, 2023
IPAM
Machine learning constitutive models of inelastic materials with microstructure
Presenter
- Reese Jones
June 6, 2023
ICERM
Bridging Machine Learning and Mathematical Modeling to Decipher Tumor heterogeneity and Therapy Resistance
Presenter
- Xiufen Zou
July 31, 2025
ICERM
Maria Schuld - How to rethink quantum machine learning - IPAM at UCLA
Presenter
- Maria Schuld
October 16, 2023
IPAM
Optimization, Sampling and Generative Modeling in Non-Euclidean Spaces
Presenter
- Molei Tao
May 15, 2024
IMSI