Samarth Sinha

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Animesh GargGeorgia Institute of Technology, University of Toronto, NvidiaVerified email at gatech.edu
Trevor DarrellProfessor of Computer Science, U.C. BerkeleyVerified email at eecs.berkeley.edu
Sayna EbrahimiSenior Research Scientist at Google DeepMindVerified email at berkeley.edu
Zeynep AkataProfessor at TUM and Director at Helmholtz MunichVerified email at helmholtz-munich.de
Anirudh GoyalGoogle DeepMind, Mila, Université de MontréalVerified email at umontreal.ca
Karsten RothELLIS, IMPRS-IS, University of TübingenVerified email at uni-tuebingen.de
Hugo LarochelleGoogle DeepMind & MilaVerified email at google.com
Edgar SchönfeldResearch Scientist at Meta GenAIVerified email at meta.com
Homanga BharadhwajCarnegie Mellon University | Google DeepMindVerified email at cs.cmu.edu
Augustus OdenaResearch ScientistVerified email at columbia.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Colin RaffelUniversity of Toronto, Vector Institute and Hugging FaceVerified email at cs.toronto.edu
Ajay MandlekarResearch Scientist, NVIDIAVerified email at nvidia.com
Aravind SrinivasCofounder and CEO, Perplexity AIVerified email at perplexity.ai
Adji Bousso DiengAssistant Professor of Computer Science, Princeton UniversityVerified email at princeton.edu
Yun-Chun ChenUniversity of TorontoVerified email at cs.toronto.edu
Haoyu XiongStanford UniversityVerified email at stanford.edu
Jiaming SongStanford UniversityVerified email at cs.stanford.edu
Florian ShkurtiAssistant Professor, Computer Science, University of TorontoVerified email at cs.toronto.edu
Andrea VedaldiUniversity of OxfordVerified email at robots.ox.ac.uk

Samarth Sinha

University of Toronto

Verified email at mail.utoronto.ca - Homepage

Deep Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Generalized Zero-and Few-Shot Learning via Aligned Variational Autoencoders E Schönfeld, S Ebrahimi, S Sinha, T Darrell, Z Akata CVPR 2019, 2018	757	2018
Variational Adversarial Active Learning S Sinha, S Ebrahimi, T Darrell ICCV 2019, 2019	669	2019
Revisiting training strategies and generalization performance in deep metric learning K Roth, T Milbich, S Sinha, P Gupta, B Ommer, JP Cohen ICML 2020, 2020	197	2020
S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning S Sinha, A Garg CoRL 2021, 2021	115*	2021
Curriculum By Smoothing S Sinha, A Garg, H Larochelle NeurIPS 2020, 2020	87*	2020
Small-GAN: Speeding Up GAN Training Using Core-sets S Sinha, H Zhang, A Goyal, Y Bengio, H Larochelle, A Odena ICML 2020, 2019	83	2019
D2rl: Deep dense architectures in reinforcement learning S Sinha, H Bharadhwaj, A Srinivas, A Garg NeurIPS 2020 DRL Workshop, 2020	71	2020
DiVA: Diverse Visual Feature Aggregation forDeep Metric Learning T Milbich, K Roth, H Bharadhwaj, S Sinha, Y Bengio, B Ommer, JP Cohen ECCV 2020, 2020	70*	2020
Consistency Regularization for Variational Auto-Encoders S Sinha, AB Dieng NeurIPS 2021, 2021	67	2021
Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos H Xiong, Q Li, YC Chen, H Bharadhwaj, S Sinha, A Garg IROS 2021, 2021	66	2021
Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples S Sinha, Z Zhao, AG ALIAS PARTH GOYAL, CA Raffel, A Odena NeurIPS 2020 33, 2020	63	2020
Experience replay with likelihood-free importance weights S Sinha, J Song, A Garg, S Ermon Learning for Dynamics and Control Conference, 110-123, 2022	55	2022
DIBS: Diversity inducing Information Bottleneck in Model Ensembles S Sinha, H Bharadhwaj, A Goyal, H Larochelle, A Garg, F Shkurti AAAI 2021, 2020	51	2020
Sparsepose: Sparse-view camera pose regression and refinement S Sinha, JY Zhang, A Tagliasacchi, I Gilitschenski, DB Lindell Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023	32	2023
Koopman q-learning: Offline reinforcement learning via symmetries of dynamics M Weissenbacher, S Sinha, A Garg, K Yoshinobu International conference on machine learning, 23645-23667, 2022	26	2022
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning T Milbich, K Roth, S Sinha, L Schmidt, M Ghassemi, B Ommer NeurIPS 2021, 2021	25	2021
Test: Test-time self-training under distribution shift S Sinha, P Gehler, F Locatello, B Schiele Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023	17	2023
Stackmix: A complementary mix algorithm J Chen, S Sinha, A Kyrillidis Uncertainty in Artificial Intelligence, 326-335, 2022	17*	2022
Common pets in 3d: Dynamic new-view synthesis of real-life deformable categories S Sinha, R Shapovalov, J Reizenstein, I Rocco, N Neverova, A Vedaldi, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023	10	2023
Keytr: Keypoint transporter for 3d reconstruction of deformable objects in videos D Novotny, I Rocco, S Sinha, A Carlier, G Kerchenbaum, R Shapovalov, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	9	2022

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