Videos

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Energy-Based Self-Supervised Learning Thumbnail

Energy-Based Self-Supervised Learning

Presenter
  • Yann LeCun
November 19, 2019
IPAM
Deep Generative Models for Molecular Graphs Thumbnail

Deep Generative Models for Molecular Graphs

Presenter
  • Nicola De Cao
September 24, 2019
IPAM
Deep Learning: Triangle Machine Learning Day - Active Learning for Probabilistic Record Linkage, Ted Enamorado Thumbnail

Deep Learning: Triangle Machine Learning Day - Active Learning for Probabilistic Record Linkage, Ted Enamorado

September 20, 2019
SAMSI
From vision models to cinema applications, and back Thumbnail

From vision models to cinema applications, and back

Presenter
  • Marcelo Bertalmio
April 5, 2019
IPAM
Enabling Reproducibility in Computational and Data-enabled Science Thumbnail

Enabling Reproducibility in Computational and Data-enabled Science

Presenter
  • Victoria Stodden
October 19, 2018
IPAM

Design of de novo biomolecular feedbacks for improved performance and robustness in living cells

Presenter
  • Guy-Bart Stan
October 4, 2017
MBI
Topological Phases in Transition Metal Chalcogenides Thumbnail

Topological Phases in Transition Metal Chalcogenides

Presenter
  • Junwei Liu
May 18, 2017
IMA
Multi-physics inversion approaches for reservoir characterization and monitoring Thumbnail

Multi-physics inversion approaches for reservoir characterization and monitoring

Presenter
  • Aria Abubakar
May 4, 2017
IPAM
Utilizing full waveform inversion from shallow to deep Thumbnail

Utilizing full waveform inversion from shallow to deep

Presenter
  • Denis Vigh
May 1, 2017
IPAM
Using random walks to analyze Prediction with Expert Advice Thumbnail

Using random walks to analyze Prediction with Expert Advice

Presenter
  • Yuval Peres
December 5, 2016
IPAM
Making Sense of Data: the Human Side of Data Analysis Thumbnail

Making Sense of Data: the Human Side of Data Analysis

Presenter
  • Danyel Fisher
April 12, 2016
IPAM
Deep learning on geometric data with intrinsic convolutional neural networks Thumbnail

Deep learning on geometric data with intrinsic convolutional neural networks

Presenter
  • Michael Bronstein
February 9, 2016
IPAM