Payel Das

papers

641

total citations

papers (12)

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models

NEURIPS 2020arXiv

citations

Larimar: Large Language Models with Episodic Memory Control

ICML 2024arXiv

citations

Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction

NEURIPS 2023arXiv

citations

Predicting Deep Neural Network Generalization with Perturbation Response Curves

NEURIPS 2021arXiv

citations

Efficient Equivariant Transfer Learning from Pretrained Models

NEURIPS 2023arXiv

citations

Mean-based Best Arm Identification in Stochastic Bandits under Reward Contamination

NEURIPS 2021arXiv

citations

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints

ICML 2024arXiv

citations

Large Language Models can Become Strong Self-Detoxifiers

ICLR 2025

citations

What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks

ICML 2024

citations

Payel Das

papers (12)

The Impact of Positional Encoding on Length Generalization in Transformers

Optimizing Mode Connectivity via Neuron Alignment

A Decentralized Parallel Algorithm for Training Generative Adversarial Nets

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models

Larimar: Large Language Models with Episodic Memory Control

Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction

Predicting Deep Neural Network Generalization with Perturbation Response Curves

Efficient Equivariant Transfer Learning from Pretrained Models

Mean-based Best Arm Identification in Stochastic Bandits under Reward Contamination

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints

Large Language Models can Become Strong Self-Detoxifiers

What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks

papers (12)

The Impact of Positional Encoding on Length Generalization in Transformers

Optimizing Mode Connectivity via Neuron Alignment

A Decentralized Parallel Algorithm for Training Generative Adversarial Nets

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models

Larimar: Large Language Models with Episodic Memory Control

Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction

Predicting Deep Neural Network Generalization with Perturbation Response Curves

Efficient Equivariant Transfer Learning from Pretrained Models

Mean-based Best Arm Identification in Stochastic Bandits under Reward Contamination

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints

Large Language Models can Become Strong Self-Detoxifiers

What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks