Payel Das
Orcid: 0000-0002-7288-0516
According to our database1,
Payel Das
authored at least 105 papers
between 2006 and 2024.
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Bibliography
2024
Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units.
J. Chem. Inf. Model., March, 2024
ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation.
CoRR, 2024
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
2023
Nat. Mac. Intell., December, 2023
Nat. Mac. Intell., June, 2023
A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening.
J. Chem. Inf. Model., May, 2023
Keeping Up with the Language Models: Robustness-Bias Interplay in NLI Data and Models.
CoRR, 2023
CoRR, 2023
Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction.
CoRR, 2023
Reprogramming Pretrained Language Models for Protein Sequence Representation Learning.
CoRR, 2023
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Direction Aware Positional and Structural Encoding for Directed Graph Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Large-scale chemical language representations capture molecular structure and properties.
Nat. Mac. Intell., December, 2022
Comput. Appl. Math., September, 2022
IEEE Trans. Signal Process., 2022
Explaining Artificial Intelligence Generation and Creativity: Human interpretability for novel ideas and artifacts.
IEEE Signal Process. Mag., 2022
Nat. Mach. Intell., 2022
Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators.
CoRR, 2022
Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions.
CoRR, 2022
CoRR, 2022
SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data.
CoRR, 2022
CoRR, 2022
CoRR, 2022
Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework.
CoRR, 2022
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
Towards Creativity Characterization of Generative Models via Group-Based Subset Scanning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations.
Proceedings of the IEEE International Conference on Acoustics, 2022
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model.
CoRR, 2021
CoRR, 2021
CoRR, 2021
Do Large Scale Molecular Language Representations Capture Important Structural Information?
CoRR, 2021
Towards creativity characterization of generative models via group-based subset scanning.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the IEEE International Symposium on Information Theory, 2021
Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the IEEE International Conference on Acoustics, 2021
ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language Models.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics.
CoRR, 2020
CoRR, 2020
Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics.
CoRR, 2020
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets.
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020
2019
Projection and multi projection methods for nonlinear integral equations on the half-line.
J. Comput. Appl. Math., 2019
CoRR, 2019
Interactive Visual Exploration of Latent Space (IVELS) for peptide auto-encoder model selection.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019
Superconvergence of Iterated Galerkin Method for a Class of Nonlinear Fredholm Integral Equations.
Proceedings of the Recent Advances in Intelligent Information Systems and Applied Mathematics, 2019
2018
Int. J. Comput. Math., 2018
CoRR, 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
2017
Proceedings of the 2017 International Workshop on Pattern Recognition in Neuroimaging, 2017
2016
J. Sci. Comput., 2016
Erratum to: Discrete Legendre spectral projection methods for Fredholm-Hammerstein integral equations [J. Comput. Appl. Math 278 (2015) 293-305].
J. Comput. Appl. Math., 2016
Corrigendum to: "Convergence analysis of discrete legendre spectral projection methods for hammerstein integral equations of mixed type" Applied Mathematics and Computation Volume 265, 15 August 2015, Pages 574-601.
Appl. Math. Comput., 2016
2015
Discrete Legendre spectral projection methods for Fredholm-Hammerstein integral equations.
J. Comput. Appl. Math., 2015
Convergence analysis of discrete legendre spectral projection methods for hammerstein integral equations of mixed type.
Appl. Math. Comput., 2015
2014
Comparative study of metamodelling techniques in building energy simulation: Guidelines for practitioners.
Simul. Model. Pract. Theory, 2014
J. Comput. Appl. Math., 2014
2011
2009
Free energy simulations reveal a double mutant avian H5N1 virus hemagglutinin with altered receptor binding specificity.
J. Comput. Chem., 2009
2006
Low-dimensional, free-energy landscapes of protein-folding reactions by nonlinear dimensionality reduction.
Proc. Natl. Acad. Sci. USA, 2006