Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders. - Edgar Schönfeld; Sayna Ebrahimi; Samarth Sinha; Trevor Darrell; Zeynep Akata (CVPR, 2019)

Generalized Zero-Shot Learning via Aligned Variational Autoencoders. - Edgar Schönfeld; Sayna Ebrahimi; Samarth Sinha; Trevor Darrell; Zeynep Akata (CVPR Workshops, 2019)

Variational Adversarial Active Learning. - Samarth Sinha; Sayna Ebrahimi; Trevor Darrell (ICCV, 2019)

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. - Timo Milbich; Karsten Roth; Homanga Bharadhwaj; Samarth Sinha; Yoshua Bengio; Björn Ommer; Joseph Paul Cohen (ECCV (8), 2020)

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. - Karsten Roth; Timo Milbich; Samarth Sinha; Prateek Gupta; Björn Ommer; Joseph Paul Cohen (ICML, 2020)

Small-GAN: Speeding up GAN Training using Core-Sets. - Samarth Sinha; Han Zhang 010; Anirudh Goyal; Yoshua Bengio; Hugo Larochelle; Augustus Odena (ICML, 2020)

Curriculum By Smoothing. - Samarth Sinha; Animesh Garg; Hugo Larochelle (NeurIPS, 2020)

Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples. - Samarth Sinha; Zhengli Zhao; Anirudh Goyal; Colin Raffel; Augustus Odena (NeurIPS, 2020)

Top-K Training of GANs: Improving Generators by Making Critics Less Critical. - Samarth Sinha; Anirudh Goyal; Colin Raffel; Augustus Odena (CoRR, 2020)

Curriculum By Texture. - Samarth Sinha; Animesh Garg; Hugo Larochelle (CoRR, 2020)

Maximum Entropy Models for Fast Adaptation. - Samarth Sinha; Anirudh Goyal; Animesh Garg (CoRR, 2020)

D2RL: Deep Dense Architectures in Reinforcement Learning. - Samarth Sinha; Homanga Bharadhwaj; Aravind Srinivas; Animesh Garg (CoRR, 2020)

ImCLR: Implicit Contrastive Learning for Image Classification. - John Chen 002; Samarth Sinha; Anastasios Kyrillidis (CoRR, 2020)

DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. - Samarth Sinha; Homanga Bharadhwaj; Anirudh Goyal; Hugo Larochelle; Animesh Garg; Florian Shkurti (AAAI, 2021)

S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning in Robotics. - Samarth Sinha; Ajay Mandlekar; Animesh Garg (CoRL, 2021)

Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos. - Haoyu Xiong; Quanzhou Li; Yun-Chun Chen; Homanga Bharadhwaj; Samarth Sinha; Animesh Garg (IROS, 2021)

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. - Timo Milbich; Karsten Roth; Samarth Sinha; Ludwig Schmidt; Marzyeh Ghassemi; Björn Ommer (NeurIPS, 2021)

Consistency Regularization for Variational Auto-Encoders. - Samarth Sinha; Adji Bousso Dieng (NeurIPS, 2021)

S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning. - Samarth Sinha; Animesh Garg (CoRR, 2021)

KeyTr: Keypoint Transporter for 3D Reconstruction of Deformable Objects in Videos. - David Novotný; Ignacio Rocco; Samarth Sinha; Alexandre Carlier; Gael Kerchenbaum; Roman Shapovalov; Nikita Smetanin; Natalia Neverova; Benjamin Graham; Andrea Vedaldi (CVPR, 2022)

Uniform Priors for Data-Efficient Learning. - Samarth Sinha; Karsten Roth; Anirudh Goyal; Marzyeh Ghassemi; Zeynep Akata; Hugo Larochelle; Animesh Garg (CVPR Workshops, 2022)

Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics. - Matthias Weissenbacher; Samarth Sinha; Animesh Garg; Yoshinobu Kawahara (ICML, 2022)

Experience Replay with Likelihood-free Importance Weights. - Samarth Sinha; Jiaming Song; Animesh Garg; Stefano Ermon (L4DC, 2022)

Stackmix: a complementary mix algorithm. - John Chen 002; Samarth Sinha; Anastasios Kyrillidis (UAI, 2022)

Offline Policy Optimization in RL with Variance Regularizaton. - Riashat Islam; Samarth Sinha; Homanga Bharadhwaj; Samin Yeasar Arnob; Zhuoran Yang; Animesh Garg; Zhaoran Wang 001; Lihong Li; Doina Precup (CoRR, 2022)

SparsePose: Sparse-View Camera Pose Regression and Refinement. - Samarth Sinha; Jason Y. Zhang 001; Andrea Tagliasacchi; Igor Gilitschenski; David B. Lindell (CVPR, 2023)

Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories. - Samarth Sinha; Roman Shapovalov; Jeremy Reizenstein; Ignacio Rocco; Natalia Neverova; Andrea Vedaldi; David Novotný (CVPR, 2023)

TeST: Test-time Self-Training under Distribution Shift. - Samarth Sinha; Peter V. Gehler; Francesco Locatello; Bernt Schiele (WACV, 2023)

Δ-Networks for Efficient Model Patching. - Chaitanya Devaguptapu; Samarth Sinha; K. J. Joseph; Vineeth N. Balasubramanian; Animesh Garg (CoRR, 2023)