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ORCIDSamarth Sinha
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2020 – today
- 2023
[c21]Samarth Sinha, Roman Shapovalov, Jeremy Reizenstein, Ignacio Rocco, Natalia Neverova, Andrea Vedaldi, David Novotný:
Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories. CVPR 2023: 4881-4891- [c20]Samarth Sinha, Jason Y. Zhang, Andrea Tagliasacchi, Igor Gilitschenski, David B. Lindell
:
SparsePose: Sparse-View Camera Pose Regression and Refinement. CVPR 2023: 21349-21359 - [c19]Samarth Sinha, Peter V. Gehler, Francesco Locatello, Bernt Schiele:
TeST: Test-time Self-Training under Distribution Shift. WACV 2023: 2758-2768 - [i22]Chaitanya Devaguptapu, Samarth Sinha, K. J. Joseph, Vineeth N. Balasubramanian, Animesh Garg:
Δ-Networks for Efficient Model Patching. CoRR abs/2303.14772 (2023) - 2022
- [c18]Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg:
Uniform Priors for Data-Efficient Learning. CVPR Workshops 2022: 4016-4027 - [c17]David Novotný, Ignacio Rocco, Samarth Sinha, Alexandre Carlier, Gael Kerchenbaum, Roman Shapovalov, Nikita Smetanin, Natalia Neverova, Benjamin Graham, Andrea Vedaldi:
KeyTr: Keypoint Transporter for 3D Reconstruction of Deformable Objects in Videos. CVPR 2022: 5585-5594 - [c16]Matthias Weissenbacher, Samarth Sinha, Animesh Garg, Yoshinobu Kawahara:
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics. ICML 2022: 23645-23667 - [c15]Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon:
Experience Replay with Likelihood-free Importance Weights. L4DC 2022: 110-123 - [c14]John Chen, Samarth Sinha, Anastasios Kyrillidis:
Stackmix: a complementary mix algorithm. UAI 2022: 326-335 - [i21]Samarth Sinha, Peter V. Gehler, Francesco Locatello, Bernt Schiele:
TeST: Test-time Self-Training under Distribution Shift. CoRR abs/2209.11459 (2022) - [i20]Samarth Sinha, Roman Shapovalov, Jeremy Reizenstein, Ignacio Rocco, Natalia Neverova, Andrea Vedaldi, David Novotný:
Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories. CoRR abs/2211.03889 (2022) - [i19]Samarth Sinha, Jason Y. Zhang, Andrea Tagliasacchi, Igor Gilitschenski, David B. Lindell:
SparsePose: Sparse-View Camera Pose Regression and Refinement. CoRR abs/2211.16991 (2022) - [i18]Riashat Islam, Samarth Sinha, Homanga Bharadhwaj, Samin Yeasar Arnob, Zhuoran Yang, Animesh Garg, Zhaoran Wang, Lihong Li, Doina Precup:
Offline Policy Optimization in RL with Variance Regularizaton. CoRR abs/2212.14405 (2022) - 2021
- [c13]Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti:
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. AAAI 2021: 9666-9674 - [c12]Samarth Sinha, Ajay Mandlekar, Animesh Garg:
S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning in Robotics. CoRL 2021: 907-917 - [c11]Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, Animesh Garg:
Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos. IROS 2021: 7827-7834 - [c10]Samarth Sinha, Adji Bousso Dieng:
Consistency Regularization for Variational Auto-Encoders. NeurIPS 2021: 12943-12954 - [c9]Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer:
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. NeurIPS 2021: 25006-25018 - [i17]Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, Animesh Garg:
Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos. CoRR abs/2101.07241 (2021) - [i16]Samarth Sinha, Animesh Garg:
S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning. CoRR abs/2103.06326 (2021) - [i15]Samarth Sinha, Adji B. Dieng:
Consistency Regularization for Variational Auto-Encoders. CoRR abs/2105.14859 (2021) - [i14]Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer:
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. CoRR abs/2107.09562 (2021) - [i13]Matthias Weissenbacher, Samarth Sinha, Animesh Garg, Yoshinobu Kawahara:
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics. CoRR abs/2111.01365 (2021) - 2020
- [c8]Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen:
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. ECCV (8) 2020: 590-607 - [c7]Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen:
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. ICML 2020: 8242-8252 - [c6]Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena:
Small-GAN: Speeding up GAN Training using Core-Sets. ICML 2020: 9005-9015 - [c5]Samarth Sinha, Animesh Garg, Hugo Larochelle:
Curriculum By Smoothing. NeurIPS 2020 - [c4]Samarth Sinha, Zhengli Zhao, Anirudh Goyal, Colin Raffel, Augustus Odena:
Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples. NeurIPS 2020 - [i12]Samarth Sinha, Anirudh Goyal, Colin Raffel, Augustus Odena:
Top-K Training of GANs: Improving Generators by Making Critics Less Critical. CoRR abs/2002.06224 (2020) - [i11]Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen:
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. CoRR abs/2002.08473 (2020) - [i10]Samarth Sinha, Animesh Garg, Hugo Larochelle:
Curriculum By Texture. CoRR abs/2003.01367 (2020) - [i9]Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti:
DIBS: Diversity inducing Information Bottleneck in Model Ensembles. CoRR abs/2003.04514 (2020) - [i8]Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen:
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. CoRR abs/2004.13458 (2020) - [i7]Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon:
Experience Replay with Likelihood-free Importance Weights. CoRR abs/2006.13169 (2020) - [i6]Samarth Sinha, Anirudh Goyal, Animesh Garg:
Maximum Entropy Models for Fast Adaptation. CoRR abs/2006.16524 (2020) - [i5]Samarth Sinha, Homanga Bharadhwaj, Aravind Srinivas, Animesh Garg:
D2RL: Deep Dense Architectures in Reinforcement Learning. CoRR abs/2010.09163 (2020) - [i4]John Chen, Samarth Sinha, Anastasios Kyrillidis:
ImCLR: Implicit Contrastive Learning for Image Classification. CoRR abs/2011.12618 (2020)
2010 – 2019
- 2019
- [c3]Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata:
Generalized Zero-Shot Learning via Aligned Variational Autoencoders. CVPR Workshops 2019: 54-57 - [c2]Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata:
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders. CVPR 2019: 8247-8255 - [c1]Samarth Sinha, Sayna Ebrahimi, Trevor Darrell:
Variational Adversarial Active Learning. ICCV 2019: 5971-5980 - [i3]Samarth Sinha, Sayna Ebrahimi, Trevor Darrell:
Variational Adversarial Active Learning. CoRR abs/1904.00370 (2019) - [i2]Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena:
Small-GAN: Speeding Up GAN Training Using Core-sets. CoRR abs/1910.13540 (2019) - 2018
- [i1]Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata:
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders. CoRR abs/1812.01784 (2018)
Coauthor Index
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