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Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling


Oct 25, 2020
Akash Srivastava, Yamini Bansal, Yukun Ding, Cole Hurwitz, Kai Xu, Bernhard Egger, Prasanna Sattigeri, Josh Tenenbaum, David D. Cox, Dan Gutfreund


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not-so-BigGAN: Generating High-Fidelity Images on a Small Compute Budget


Sep 09, 2020
Seungwook Han, Akash Srivastava, Cole Hurwitz, Prasanna Sattigeri, David D. Cox


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Sequential Transfer Machine Learning in Networks: Measuring the Impact of Data and Neural Net Similarity on Transferability


Mar 29, 2020
Robin Hirt, Akash Srivastava, Carlos Berg, Niklas Kühl


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SimVAE: Simulator-Assisted Training forInterpretable Generative Models


Nov 19, 2019
Akash Srivastava, Jessie Rosenberg, Dan Gutfreund, David D. Cox


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BreGMN: scaled-Bregman Generative Modeling Networks


Jun 01, 2019
Akash Srivastava, Kristjan Greenewald, Farzaneh Mirzazadeh


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Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference


May 29, 2019
Cole L. Hurwitz, Kai Xu, Akash Srivastava, Alessio Paolo Buccino, Matthias Hennig


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HOUDINI: Lifelong Learning as Program Synthesis


Oct 28, 2018
Lazar Valkov, Dipak Chaudhari, Akash Srivastava, Charles Sutton, Swarat Chaudhuri


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Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam


Aug 02, 2018
Mohammad Emtiyaz Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, Akash Srivastava

* Thirty-fifth International Conference on Machine Learning, 2018 
* Camera ready version 

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Ratio Matching MMD Nets: Low dimensional projections for effective deep generative models


May 31, 2018
Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton

* Code: https://github.com/akashgit/RM-MMDnet 

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Variational Inference In Pachinko Allocation Machines


Apr 21, 2018
Akash Srivastava, Charles Sutton


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VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning


Nov 06, 2017
Akash Srivastava, Lazar Valkov, Chris Russell, Michael U. Gutmann, Charles Sutton

* Published as a conference paper at NIPS, 2017 

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Autoencoding Variational Inference For Topic Models


Mar 04, 2017
Akash Srivastava, Charles Sutton


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Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation


Jun 19, 2016
Akash Srivastava, James Zou, Ryan P. Adams, Charles Sutton

* presented at 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016), New York, NY 

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