SAMARTH SINHA

samarth [dot] sinha [at] mail [dot] utoronto [dot] ca

I am a final year undergraduate student in Computer Engineering at the University of Toronto and Vector Institute where I work with Animesh Garg on the intersection of Reinforcement Learning and Computer Vision.

Previously, I was a visiting student at MILA working closely with Anirudh Goyal, Hugo Larochelle and Yoshua Bengio; I was also a visitor at UC Berkeley, working with Trevor Darrell and Zeynep Akata. I have also been very fortunate to work at some amazing startups: AuroraDeepMapConcuredNanoleaf

I spent my high school summers working with Alex Lvovsky working on Quantum Optics and with Guenther Ruhe working on Software Engineering. 

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RECENT UPDATES

  • [July 2021] One paper accepted to IROS 2021! ✨

  • [June 2021] Finished undergrad at Toronto 🎓

  • [May 2021] Started internship at Amazon Research! 📝

  • [Dec 2020] One paper accepted to AAAI 2021! ✨

  • [Sept 2020] Two papers accepted to NeurIPS 2020, one as poster and one as a Spotlight! ✨

  • [July 2020] One paper accepted to ECCV 2020! ✨

  • [May 2020] Stared as a student researcher at the Vector Institute

  • [April 2020] Two papers accepted to ICML 2020! ✨

  • [June 2019] One paper accepted to ICCV 2019 as an oral! ✨

  • [May 2019] Started as a visiting student at MILA 

  • [March 2019] One paper accepted to CVPR 2019! ✨

  • [May 2018] Started as a visiting student at UC Berkeley 

 
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RESEARCH INTERESTS

My research interests span across Deep Learning and Deep Reinforcement Learning. I am interested in training agents that can learn generalizable representations from data.

I have had the privilege to work with some amazing collaborators, and I am always looking for new students and collaborators. If you are interested in any paper on the website, please get in touch!

 

PUBLICATIONS

CONSISTENCY REGULARIZATION FOR VARIATIONAL AUTOENCODERS

Samarth Sinha, Adji B. Dieng (preprint)

Samarth Sinha, Ajay Mandlekar, Animesh Garg (preprint)

Samarth Sinha*, Karsten Roth*, Anirudh Goyal, Marzyeh Ghassemi, Hugo Larochelle, Animesh Garg

NeurIPS Meta Learning Workshop 2020

Samarth Sinha*, Jiaming Song*, Animesh Garg, Stefano Ermon (preprint)

STACKMIX: A COMPLIMENTARY MIX ALGORITHM

John Chen, Samarth Sinha, Anastasios Kyrillidis (preprint)

Samarth Sinha*, Homanga Bharadhwaj*, Aravind Srinivas, Animesh Garg

NeurIPS Deep RL Workshop 2020

Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, Animesh Garg

IROS 2021 (Poster)

Samarth Sinha*, Homanga Bharadhwaj*, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti

AAAI 2021 (Poster)

Samarth Sinha, Animesh Garg, Hugo Larochelle 

NeurIPS 2021 (Spotlight)

Samarth Sinha*, Zhengli Zhao*, Anirudh Goyal, Colin Raffel, Augustus Odena 

NeurIPS 2020 (Poster)

Karsten Roth*, Timo Milbich*, Homanga Bharadhwaj, Samarth Sinha, Joseph Paul Cohen, Bjorn Ommer, Yoshua Bengio

ECCV 2020

Karsten Roth*, Timo Milbich*, Samarth Sinha, Prateek Gupta, Bjoern Ommer, Joseph Paul Cohen

ICML 2020 (Poster)

Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena 
ICML 2020 (Poster)

Samarth Sinha*, Sayna Ebrahimi*, Trevor Darrell

ICCV 2019 (Oral)

Edgar Schönfeld, Sayna Ebrahimi, Samarth SinhaTrevor Darrell, Zeynep Akata 

CVPR 2019 (Poster)