Accelerating atomic-scale calculations with machine learning

Andrew Peterson
Brown University
February 20, 2019
Theory and Practice in Machine Learning and Computer Vision
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Mad Max - Affine Spline Insights into Deep Learning

Richard Baraniuk
Rice University
February 20, 2019
Theory and Practice in Machine Learning and Computer Vision
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Learning with Little Data

Rich Zemel
University of Toronto
February 20, 2019
Theory and Practice in Machine Learning and Computer Vision
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Towards Joint Understanding of Images and Language

Svetlana Lazebnik
University of Illinois, Urbana-Champaign
February 19, 2019
Theory and Practice in Machine Learning and Computer Vision
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Mathematics of Deep Learning

Rene Vidal
Johns Hopkins University
February 19, 2019
Theory and Practice in Machine Learning and Computer Vision
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Analyzing Optimization in Deep Learning via Trajectories

Nadav Cohen
Institute for Advanced Study
February 19, 2019
Theory and Practice in Machine Learning and Computer Vision
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Learning to Optimize Multigrid PDE Solvers

Ronen Basri
Weizmann Institute of Science
February 18, 2019
Theory and Practice in Machine Learning and Computer Vision
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Stochastic Video Generation with a Learned Prior

Rob Fergus
Courant Institute of Mathematical Sciences, New York University
February 18, 2019
Theory and Practice in Machine Learning and Computer Vision
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Strong-Weak Adversarial Domain Adaptation

Kate Saenko
Boston University
February 18, 2019
Theory and Practice in Machine Learning and Computer Vision
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