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An overview of hybrid physics/machine learning modelling at Michelin: from rubber manufacturing simulation to real-time tire performance prediction opportunities
Presenter
- Raphael Meunier
December 1, 2025
IMSI
Plethysm, symmetric chain decompositions and Erhart polynomials
Presenter
- Mike Zabrocki
September 15, 2025
ICERM
Rate-Distortion Theoretical Views of Bayesian Learning Coefficients
Presenter
- Kazuho Watanabe
December 11, 2023
IMSI
Louis Schatzki - Quantum Statistical Query Learning II of II - IPAM at UCLA
Presenter
- Louis Schatzki
October 19, 2023
IPAM
Hsin-Yuan (Robert) Huang - Learning to predict arbitrary quantum processes - IPAM at UCLA
Presenter
- Hsin-Yuan Huang
October 18, 2023
IPAM
Maria Schuld - How to rethink quantum machine learning - IPAM at UCLA
Presenter
- Maria Schuld
October 16, 2023
IPAM
George Barbastathis - On the use of machine learning for computational imaging - IPAM at UCLA
Presenter
- George Barbastathis
October 11, 2022
IPAM
Applications of machine learning in low-latency electromagnetic counterpart inference from gravitational waves
Presenter
- Deep Chatterjee
November 29, 2021
IPAM
How to allow deep learning on your data without revealing your data
Presenter
- Sanjeev Arora
February 25, 2021
IPAM
Low-rank matrix recovery from quantized or count observations
Presenter
- Mark Davenport
September 11, 2020
IAS
Towards a low-cost scalable data-driven modeling of coupled systems and non-stationary time series analysis
Presenter
- Lukas Pospisil
November 1, 2019
IPAM