Videos

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Heather Kulik - Exploring multi-million compound spaces w/ chemical accuracy using machine learning Thumbnail

Heather Kulik - Exploring multi-million compound spaces w/ chemical accuracy using machine learning

Presenter
  • Heather Kulik
March 27, 2023
IPAM
Molecular design blueprints: materials and catalysts from new simulation and machine learning tools Thumbnail

Molecular design blueprints: materials and catalysts from new simulation and machine learning tools

Presenter
  • Heather Kulik
October 15, 2019
IPAM
2 Case Studies Thumbnail

2 Case Studies

Presenters
  • Tuhin Sahai
  • Sumanth Swaminathan
April 20, 2015
IMA
Quantum-Chemical Predictions from Coarse-Grained Molecular Representations Thumbnail

Quantum-Chemical Predictions from Coarse-Grained Molecular Representations

Presenter
  • Nick Jackson
April 23, 2024
IMSI
Toward accurate, efficient, and reliable interatomic potentials Thumbnail

Toward accurate, efficient, and reliable interatomic potentials

Presenter
  • Alexander Shapeev
November 16, 2016
IPAM
The Spread of Misinformation in Social Media Thumbnail

The Spread of Misinformation in Social Media

Presenter
  • Filippo Menczer
May 13, 2016
IPAM
Max Kleiman-Weiner - Multi-Agent Common Sense Thumbnail

Max Kleiman-Weiner - Multi-Agent Common Sense

Presenter
  • Max Kleiman-Weiner
February 16, 2022
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
Deep Neural Networks Motivated By Differential Equations (Part 1/2) Thumbnail

Deep Neural Networks Motivated By Differential Equations (Part 1/2)

Presenter
  • Lars Ruthotto
September 9, 2019
IPAM
Towards a Science of Security Games: Key Algorithmic Principles, Deployed Applications and Research Challenges Thumbnail

Towards a Science of Security Games: Key Algorithmic Principles, Deployed Applications and Research Challenges

Presenter
  • Milind Tambe
July 23, 2015
IPAM
Deep Learning for Combinatorial Optimization: count your flops and make your flops count! Thumbnail

Deep Learning for Combinatorial Optimization: count your flops and make your flops count!

Presenter
  • Wouter Kool
February 24, 2021
IPAM
Using autoencoders as generative models to create forecast ensembles for data assimilation Thumbnail

Using autoencoders as generative models to create forecast ensembles for data assimilation

Presenter
  • Ian Grooms
October 31, 2022
IMSI