Videos

Start date cannot be after end date.
Metric learning for persistence-based summaries and application to graph classification Thumbnail

Metric learning for persistence-based summaries and application to graph classification

Presenter
  • Yusu Wang
April 29, 2019
IPAM

Learning Discrete Markov Random Fields with Nearly Optimal Runtime and Sample Complexity

Presenter
  • Adam Klivans
March 20, 2019
ICERM

Learned Visual Sensors and Probabilistic Measurements

Presenter
  • Ayan Chakrabarti
March 19, 2019
ICERM

Towards Joint Understanding of Images and Language

Presenter
  • Svetlana Lazebnik
February 19, 2019
ICERM

Partial Differential Equations Approaches to Optimization and Regularization of Deep Neural Networks

Presenter
  • Adam Oberman
November 2, 2018
ICERM
Learning low-dimensional models: Nonlinear model reduction via lifting transformations and proper orthogonal decomposition Thumbnail

Learning low-dimensional models: Nonlinear model reduction via lifting transformations and proper orthogonal decomposition

Presenter
  • Karen Willcox
October 15, 2018
IPAM
Deep Learning for Science: current status and future directions Thumbnail

Deep Learning for Science: current status and future directions

Presenter
  • Mr Prabhat
September 18, 2018
IPAM
On Expressiveness and Optimization in Deep Learning Thumbnail

On Expressiveness and Optimization in Deep Learning

Presenter
  • Nadav Cohen
April 2, 2018
IAS
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II

Presenter
  • Russell Impagliazzo
November 14, 2017
IAS
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I

Presenter
  • Russell Impagliazzo
November 13, 2017
IAS
Learning dynamics with dynamical distances: From diffusion maps to commute maps and coherence Thumbnail

Learning dynamics with dynamical distances: From diffusion maps to commute maps and coherence

Presenter
  • Ralf Banisch
December 5, 2016
IPAM
Explaining and Understanding Non-linear Classifier Decisions with Application to Deep Learning Thumbnail

Explaining and Understanding Non-linear Classifier Decisions with Application to Deep Learning

Presenter
  • Klaus-Robert Müller
November 18, 2016
IPAM