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Likelihood Ratio Exponential Families

Jan 15, 2021
Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg

* NeurIPS Workshop on Deep Learning through Information Geometry 

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Annealed Importance Sampling with q-Paths

Dec 14, 2020
Rob Brekelmans, Vaden Masrani, Thang Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen

* NeurIPS Workshop on Deep Learning through Information Geometry (Best Paper Award) 

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Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective

Oct 31, 2020
Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood

* NeurIPS 2020 

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Gaussian Process Bandit Optimization of theThermodynamic Variational Objective

Oct 29, 2020
Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood

* NeurIPS 2020 

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All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference

Jul 01, 2020
Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan

* ICML 2020 

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Discovery and Separation of Features for Invariant Representation Learning

Dec 02, 2019
Ayush Jaiswal, Rob Brekelmans, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan

* 10 pages, 3 figures 

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Exact Rate-Distortion in Autoencoders via Echo Noise

Apr 15, 2019
Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg


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Invariant Representations without Adversarial Training

Nov 04, 2018
Daniel Moyer, Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan

* NIPS 2018 camera-ready version 

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Auto-Encoding Total Correlation Explanation

Feb 16, 2018
Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan


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Disentangled Representations via Synergy Minimization

Oct 10, 2017
Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan

* 8 pages, 4 figures, 55th Annual Allerton Conference on Communication, Control, and Computing, 2017 

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