Videos

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Deep Generative Models for Molecular Graphs Thumbnail

Deep Generative Models for Molecular Graphs

Presenter
  • Nicola De Cao
September 24, 2019
IPAM
New horizons in quantum biology: Learning complexity, emergence, and coherence in living matter Thumbnail

New horizons in quantum biology: Learning complexity, emergence, and coherence in living matter

Presenter
  • Philip Kurian
September 24, 2019
IPAM
Deep Generative Learning for Physics Many-Body Systems Thumbnail

Deep Generative Learning for Physics Many-Body Systems

Presenter
  • Frank Noe
September 23, 2019
IPAM
A primer on normalizing flows Thumbnail

A primer on normalizing flows

Presenter
  • Laurent Dinh
September 23, 2019
IPAM
Physics-Informed (and -informative) Generative Modelling in Astronomy Thumbnail

Physics-Informed (and -informative) Generative Modelling in Astronomy

Presenter
  • Joshua Bloom
September 23, 2019
IPAM
Graph Convolutional Neural Networks for Molecule Generation Thumbnail

Graph Convolutional Neural Networks for Molecule Generation

Presenter
  • Xavier Bresson
September 23, 2019
IPAM
Machine Learning of Quantum Chemical Space Thumbnail

Machine Learning of Quantum Chemical Space

Presenter
  • Alexandre Tkatchenko
September 23, 2019
IPAM
Connection between Statistics and Machine Learning Thumbnail

Connection between Statistics and Machine Learning

Presenter
  • Frank Noe
September 10, 2019
IPAM
Introduction to Fluid Mechanics Thumbnail

Introduction to Fluid Mechanics

Presenter
  • Steve Brunton
September 10, 2019
IPAM
Deep Neural Networks Motivated By Differential Equations (Part 2/2) Thumbnail

Deep Neural Networks Motivated By Differential Equations (Part 2/2)

Presenter
  • Lars Ruthotto
September 10, 2019
IPAM
The interplay between physically motivated simulations and machine learning Thumbnail

The interplay between physically motivated simulations and machine learning

Presenter
  • Kyle Cranmer
September 9, 2019
IPAM
Machine learning-enabled enhanced sampling in biomolecular simulation and data-driven design of self-assembling photonic crystals and optoelectonic π-conjugated oligopeptides Thumbnail

Machine learning-enabled enhanced sampling in biomolecular simulation and data-driven design of self-assembling photonic crystals and optoelectonic π-conjugated oligopeptides

Presenter
  • Andrew Ferguson
September 9, 2019
IPAM