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From Classical Statistics to Modern ML: the Lessons of Deep Learning
Presenter
- Mikhail Belkin
October 16, 2019
IAS
Exploiting the 3D Geometry and the Structure of the World in Deep Learning
Presenter
- Ersin Yumer
May 24, 2019
IPAM
Topological transitions (and symmetries) of input representations in Deep Learning
Presenter
- Naftali Tishby
May 1, 2019
IPAM
Towards demystifying over-parameterization and early stopping in deep learning
Presenter
- Mahdi Soltanolkotabi
May 1, 2019
IPAM
Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling and computation under uncertainty
Presenter
- Paris Perdikaris
September 28, 2018
IPAM
Representations of High Dimensional Data 07/13/18 - Introduction to Deep Learning
July 13, 2018
SLMath
New Techniques in Optimization and Their Applications to Deep Learning and Related Inverse Problems
Presenter
- Stanley Osher
February 8, 2018
IPAM
Unraveling the mysteries of stochastic gradient descent on deep neural networks
Presenter
- Pratik Chaudhari
February 8, 2018
IPAM
Public Lecture: AI Breakthroughs & Obstacles to Progress, Mathematical and Otherwise
Presenter
- Yann LeCun
February 6, 2018
IPAM
Beyond the second timescale in all-atom MD: shallow and deep kinetic models for biomolecules
Presenter
- Frank Noé
October 31, 2017
IPAM
Lipschitz bounds for general convolutional neural networks
Presenter
- Dongmian Zou
September 26, 2017
IMA