Samarth Sinha | DeepAI

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∙ 03/26/2023

Δ-Networks for Efficient Model Patching

Models pre-trained on large-scale datasets are often finetuned to suppor...

0 Chaitanya Devaguptapu, et al. ∙

∙ 12/29/2022

Offline Policy Optimization in RL with Variance Regularizaton

Learning policies from fixed offline datasets is a key challenge to scal...

0 Riashat Islam, et al. ∙

∙ 11/29/2022

SparsePose: Sparse-View Camera Pose Regression and Refinement

Camera pose estimation is a key step in standard 3D reconstruction pipel...

1 Samarth Sinha, et al. ∙

∙ 11/07/2022

Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories

Obtaining photorealistic reconstructions of objects from sparse views is...

0 Samarth Sinha, et al. ∙

∙ 09/23/2022

TeST: Test-time Self-Training under Distribution Shift

Despite their recent success, deep neural networks continue to perform p...

0 Samarth Sinha, et al. ∙

∙ 11/02/2021

Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics

Offline reinforcement learning leverages large datasets to train policie...

0 Matthias Weissenbacher, et al. ∙

∙ 07/20/2021

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning

Deep Metric Learning (DML) aims to find representations suitable for zer...

17 Timo Milbich, et al. ∙

∙ 05/31/2021

Consistency Regularization for Variational Auto-Encoders

Variational auto-encoders (VAEs) are a powerful approach to unsupervised...

0 Samarth Sinha, et al. ∙

∙ 03/10/2021

S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning

Offline reinforcement learning proposes to learn policies from large col...

0 Samarth Sinha, et al. ∙

∙ 01/18/2021

Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos

We present an approach for physical imitation from human videos for robo...

7 Haoyu Xiong, et al. ∙

∙ 11/25/2020

ImCLR: Implicit Contrastive Learning for Image Classification

Contrastive learning is an effective method for learning visual represen...

0 John Chen, et al. ∙

∙ 10/19/2020

D2RL: Deep Dense Architectures in Reinforcement Learning

While improvements in deep learning architectures have played a crucial ...

0 Samarth Sinha, et al. ∙

∙ 06/30/2020

Maximum Entropy Models for Fast Adaptation

Deep Neural Networks have shown great promise on a variety of downstream...

12 Samarth Sinha, et al. ∙

∙ 06/23/2020

Experience Replay with Likelihood-free Importance Weights

The use of past experiences to accelerate temporal difference (TD) learn...

12 Samarth Sinha, et al. ∙

∙ 04/28/2020

DiVA: Diverse Visual Feature Aggregation forDeep Metric Learning

Visual Similarity plays an important role in many computer vision applic...

3 Timo Milbich, et al. ∙

∙ 04/28/2020

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning

Visual Similarity plays an important role in many computer vision applic...

0 Timo Milbich, et al. ∙

∙ 03/10/2020

DIBS: Diversity inducing Information Bottleneck in Model Ensembles

Although deep learning models have achieved state-of-the-art performance...

7 Samarth Sinha, et al. ∙

∙ 03/03/2020

Curriculum By Texture

Convolutional Neural Networks (CNNs) have shown impressive performance i...

5 Samarth Sinha, et al. ∙

∙ 02/19/2020

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning

Deep Metric Learning (DML) is arguably one of the most influential lines...

0 Karsten Roth, et al. ∙

∙ 02/14/2020

Top-K Training of GANs: Improving Generators by Making Critics Less Critical

We introduce a simple (one line of code) modification to the Generative ...

16 Samarth Sinha, et al. ∙

∙ 10/29/2019

Small-GAN: Speeding Up GAN Training Using Core-sets

Recent work by Brock et al. (2018) suggests that Generative Adversarial ...

22 Samarth Sinha, et al. ∙

∙ 03/31/2019

Variational Adversarial Active Learning

Active learning aims to develop label-efficient algorithms by sampling t...

0 Samarth Sinha, et al. ∙

∙ 12/05/2018

Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

Many approaches in generalized zero-shot learning rely on cross-modal ma...

0 Edgar Schönfeld, et al. ∙

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