← Authors

Samarth Sinha

18 papers · 2019–2023 · 10 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (45) 🧭 Keyword Pioneer 🌍 Conference Polyglot (10) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (5) πŸ—ƒοΈ Keyword Collector (87) πŸ’Ž Century Club (18) πŸ”₯ Unstoppable (5) ⚑ Prolific Year (5)

Conferences

CVPR (4) NIPS (4) ICML (3) AAAI (1) CORL (1) ECCV (1) ICCV (1) L4DC (1) UAI (1) WACV (1)

Top co-authors

Animesh Garg (5) Hugo Larochelle (3) Timo Milbich (3) Bjorn Ommer (3) Karsten Roth (3) Ignacio Rocco (2) Anirudh Goyal (2) Sayna Ebrahimi (2) Augustus Odena (2) Trevor Darrell (2)

Research topics

Reinforcement Learning (1)

Keywords

representation learning (3) variational autoencoder (3) data augmentation (3) 3d reconstruction (3) offline reinforcement learning (2) semi-supervised learning (2) deformable object (2) latent space (2) generative adversarial network (2) few-shot learning (2) convolutional neural network (2) distribution shift (2) active learning (2) latent representation (2) deep metric learning (2) domain adaptation (1) variational inference (1) benchmark evaluation (1) image generation (1) image segmentation (1)

Papers

TeST: Test-Time Self-Training Under Distribution Shift WACV 2023
SparsePose: Sparse-View Camera Pose Regression and Refinement CVPR 2023
Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories CVPR 2023
KeyTr: Keypoint Transporter for 3D Reconstruction of Deformable Objects in Videos CVPR 2022
Stackmix: a complementary mix algorithm UAI 2022
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics ICML 2022
Experience Replay with Likelihood-free Importance Weights L4DC 2022
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning NIPS 2021
S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning in Robotics CORL 2021
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles AAAI 2021
Consistency Regularization for Variational Auto-Encoders NIPS 2021
Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples NIPS 2020
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning ICML 2020
Small-GAN: Speeding up GAN Training using Core-Sets ICML 2020
Curriculum By Smoothing NIPS 2020
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning ECCV 2020
Variational Adversarial Active Learning ICCV 2019
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders CVPR 2019