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Reliable predictions? Counterfactual predictions? Equitable treatment? Some recent progress in predictive inference
Presenter
- Emmanuel Candes
April 11, 2021
ICERM
Can we design deep learning models that are inherently interpretable?
Presenter
- Cynthia Rudin
April 11, 2021
ICERM
Deep Learning for Combinatorial Optimization: count your flops and make your flops count!
Presenter
- Wouter Kool
February 24, 2021
IPAM
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
Presenter
- Sammy Wu Fung
May 5, 2020
SLMath
Direct and dual Information Bottleneck frameworks for Deep Learning
Presenter
- Tali Tishby
February 24, 2020
IAS
Convolutional autoencoders and LSTMs - using deep learning to overcome Kolmogorov-width limitations and accurately model errors in nonlinear model reduction
Presenter
- Kevin Carlberg
February 21, 2020
ICERM
Deep Learning of dynamical systems for mechanistic insight and prediction in psychiatry
Presenter
- Daniel Durstewitz
February 18, 2020
IPAM
Deep Learning-based MR Image Reconstruction and Contrast Conversion
Presenter
- Dosik Hwang
January 28, 2020
IPAM
Machine learning for molecular simulations: priors and predictive constraints
Presenter
- Tristan Bereau
October 18, 2019
IPAM
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