Samarth Sinha

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 43

Top Topics

Deformable Objects

Information Bottleneck

Reinforcement Learning

Maximum Entropy

Top Venues

Publications

Chaitanya Devaguptapu, Samarth Sinha, K. J. Joseph, Vineeth N. Balasubramanian, Animesh Garg
Δ-Networks for Efficient Model Patching. CoRR (2023)
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)
Samarth Sinha, Jason Y. Zhang, Andrea Tagliasacchi, Igor Gilitschenski, David B. Lindell
SparsePose: Sparse-View Camera Pose Regression and Refinement. CVPR (2023)
Samarth Sinha, Peter V. Gehler, Francesco Locatello, Bernt Schiele
TeST: Test-time Self-Training under Distribution Shift. WACV (2023)
John Chen, Samarth Sinha, Anastasios Kyrillidis
Stackmix: a complementary mix algorithm. UAI (2022)
Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg
Uniform Priors for Data-Efficient Learning. CVPR Workshops (2022)
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 (2022)
Matthias Weissenbacher, Samarth Sinha, Animesh Garg, Yoshinobu Kawahara
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics. ICML (2022)
Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon
Experience Replay with Likelihood-free Importance Weights. L4DC (2022)
Samarth Sinha, Jason Y. Zhang, Andrea Tagliasacchi, Igor Gilitschenski, David B. Lindell
SparsePose: Sparse-View Camera Pose Regression and Refinement. CoRR (2022)
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 (2022)
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)
Samarth Sinha, Peter V. Gehler, Francesco Locatello, Bernt Schiele
TeST: Test-time Self-Training under Distribution Shift. CoRR (2022)
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)
Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. CoRR (2021)
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)
Samarth Sinha, Adji B. Dieng
Consistency Regularization for Variational Auto-Encoders. CoRR (2021)
Matthias Weissenbacher, Samarth Sinha, Animesh Garg, Yoshinobu Kawahara
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics. CoRR (2021)
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. AAAI (2021)
Samarth Sinha, Adji Bousso Dieng
Consistency Regularization for Variational Auto-Encoders. NeurIPS (2021)
Samarth Sinha, Ajay Mandlekar, Animesh Garg
S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning in Robotics. CoRL (2021)
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 (2021)
Samarth Sinha, Animesh Garg
S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning. CoRR (2021)
Samarth Sinha, Anirudh Goyal, Colin Raffel, Augustus Odena
Top-K Training of GANs: Improving Generators by Making Critics Less Critical. CoRR (2020)
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)
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
DIBS: Diversity inducing Information Bottleneck in Model Ensembles. CoRR (2020)
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 (2020)
Samarth Sinha, Animesh Garg, Hugo Larochelle
Curriculum By Smoothing. NeurIPS (2020)
Samarth Sinha, Animesh Garg, Hugo Larochelle
Curriculum By Texture. CoRR (2020)
Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. CoRR (2020)
Samarth Sinha, Homanga Bharadhwaj, Aravind Srinivas, Animesh Garg
D2RL: Deep Dense Architectures in Reinforcement Learning. CoRR (2020)
John Chen, Samarth Sinha, Anastasios Kyrillidis
ImCLR: Implicit Contrastive Learning for Image Classification. CoRR (2020)
Samarth Sinha, Anirudh Goyal, Animesh Garg
Maximum Entropy Models for Fast Adaptation. CoRR (2020)
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)
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)
Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon
Experience Replay with Likelihood-free Importance Weights. CoRR (2020)
Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
Small-GAN: Speeding up GAN Training using Core-Sets. ICML (2020)
Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
Small-GAN: Speeding Up GAN Training Using Core-sets. CoRR (2019)
Samarth Sinha, Sayna Ebrahimi, Trevor Darrell
Variational Adversarial Active Learning. ICCV (2019)
Samarth Sinha, Sayna Ebrahimi, Trevor Darrell
Variational Adversarial Active Learning. CoRR (2019)
Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders. CVPR (2019)
Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata
Generalized Zero-Shot Learning via Aligned Variational Autoencoders. CVPR Workshops (2019)
Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders. CoRR (2018)