Videos

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

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

Presenter
  • Joshua Bloom
September 23, 2019
IPAM
On the Implicit Bias of Dropout Thumbnail

On the Implicit Bias of Dropout

Presenter
  • Rene Vidal
May 23, 2019
IPAM
Bridging Deep Neural Networks and Differential Equations for Image Analysis and Beyond Thumbnail

Bridging Deep Neural Networks and Differential Equations for Image Analysis and Beyond

Presenter
  • Bin Dong
May 1, 2019
IPAM
A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression Thumbnail

A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression

Presenter
  • Xiaoye Li
September 26, 2018
IPAM
Keynote: Recent advances in outcome weighted learning for precision medicine Thumbnail

Keynote: Recent advances in outcome weighted learning for precision medicine

Presenter
  • Michael Kosorok
September 15, 2017
IMA

Modeling the Crosstalk for the High-throughput DNA Sequencing Data

Presenter
  • Lin Wan
October 4, 2016
MBI
Quantum Mechanics, Chemical Space, and Machine Learning Thumbnail

Quantum Mechanics, Chemical Space, and Machine Learning

September 27, 2016
IPAM
Deep Learning for Many-Particle Systems Thumbnail

Deep Learning for Many-Particle Systems

Presenter
  • Pierre Baldi
February 27, 2015
IPAM
Learning Acid/Base Strength Thumbnail

Learning Acid/Base Strength

Presenter
  • Paul Ayers
February 27, 2015
IPAM
Many Particles, Collective Variables, and Machine Learning Thumbnail

Many Particles, Collective Variables, and Machine Learning

Presenter
  • Alexandre Tkatchenko
February 24, 2015
IPAM
An Introduction to Deep Learning for Vision Thumbnail

An Introduction to Deep Learning for Vision

Presenter
  • Rob Fergus
July 30, 2013
IPAM
Extracting insight from large networks: small-scale structures, large-scale structures, and their implications for machine learning and data analysis Thumbnail

Extracting insight from large networks: small-scale structures, large-scale structures, and their implications for machine learning and data analysis

Presenter
  • Michael Mahoney
October 25, 2011
IMA