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D2RL: Deep Dense Architectures in Reinforcement Learning

Oct 19, 2020
Samarth Sinha, Homanga Bharadhwaj, Aravind Srinivas, Animesh Garg


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Maximum Entropy Models for Fast Adaptation

Jun 30, 2020
Samarth Sinha, Anirudh Goyal, Animesh Garg


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Experience Replay with Likelihood-free Importance Weights

Jun 23, 2020
Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon


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DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning

Apr 29, 2020
Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen

* 18 pages 

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Revisiting Training Strategies and Generalization Performance in Deep Metric Learning

Mar 12, 2020
Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen


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DIBS: Diversity inducing Information Bottleneck in Model Ensembles

Mar 10, 2020
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti

* Samarth Sinha* and Homanga Bharadhwaj* contributed equally to this work. Code will be released at https://github.com/rvl-lab-utoronto/dibs 

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Curriculum By Texture

Mar 03, 2020
Samarth Sinha, Animesh Garg, Hugo Larochelle


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Top-K Training of GANs: Improving Generators by Making Critics Less Critical

Feb 14, 2020
Samarth Sinha, Anirudh Goyal, Colin Raffel, Augustus Odena


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Small-GAN: Speeding Up GAN Training Using Core-sets

Oct 29, 2019
Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena


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Variational Adversarial Active Learning

Mar 31, 2019
Samarth Sinha, Sayna Ebrahimi, Trevor Darrell

* First two authors contributed equally 

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Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

Dec 17, 2018
Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata

* Corrected typos 

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