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Equivariant Contrastive Learning



Rumen Dangovski , Li Jing , Charlotte Loh , Seungwook Han , Akash Srivastava , Brian Cheung , Pulkit Agrawal , Marin Soljačić

* 17 pages, 5 figures 

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



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



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



Robin Hirt , Akash Srivastava , Carlos Berg , Niklas Kühl


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SimVAE: Simulator-Assisted Training forInterpretable Generative Models



Akash Srivastava , Jessie Rosenberg , Dan Gutfreund , David D. Cox


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BreGMN: scaled-Bregman Generative Modeling Networks



Akash Srivastava , Kristjan Greenewald , Farzaneh Mirzazadeh


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Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference



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


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HOUDINI: Lifelong Learning as Program Synthesis



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



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



Akash Srivastava , Kai Xu , Michael U. Gutmann , Charles Sutton

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

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