Payel Das - RankMe

157 papers A* 33B 1Misc 4Journal 106Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	GP-MoLFormer-Sim: Test Time Molecular Optimization Through Contextual Similarity Guidance. AAAI Jirí Navrátil, Jarret Ross, Payel Das, Youssef Mroueh, Samuel C. Hoffman, Vijil Chenthamarakshan, Brian Belgodere
2025	J	`jnl`	'I often get tempted ...... to use mobile food apps': understanding the perceived utility of mobile food apps. Int. J. Bus. Inf. Syst. Santanu Mandal, R. Radhika, Swetha Sunil Kumar, Payel Das
2025	A*	`conf`	Aligning Protein Conformation Ensemble Generation with Physical Feedback. ICML Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
2025	J	`jnl`	Aligning Protein Conformation Ensemble Generation with Physical Feedback. CoRR Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
2025	A*	`conf`	Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction To Generation and Beyond. IJCAI Kehan Guo, Yili Shen, Gisela Abigail Gonzalez-Montiel, Yue Huang, Yujun Zhou, Mihir Surve, Zhichun Guo, Payel Das, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
2025	J	`jnl`	Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond. CoRR Kehan Guo, Yili Shen, Gisela Abigail Gonzalez-Montiel, Yue Huang, Yujun Zhou, Mihir Surve, Zhichun Guo, Payel Das, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
2025	J	`jnl`	Can Memory-Augmented Language Models Generalize on Reasoning-in-a-Haystack Tasks? CoRR Payel Das, Ching-Yun Ko, Sihui Dai, Georgios Kollias, Subhajit Chaudhury, Aurélie C. Lozano
2025	—	`conf`	Combining Domain and Alignment Vectors Provides Better Knowledge-Safety Trade-offs in LLMs. ACL (2) Megh Thakkar, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
2025	—	`conf`	EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts. ACL (1) Subhajit Chaudhury, Payel Das, Sarathkrishna Swaminathan, Georgios Kollias, Elliot Nelson, Khushbu Pahwa, Tejaswini Pedapati, Igor Melnyk, Matthew Riemer
2025	J	`jnl`	EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts. CoRR Subhajit Chaudhury, Payel Das, Sarathkrishna Swaminathan, Georgios Kollias, Elliot Nelson, Khushbu Pahwa, Tejaswini Pedapati, Igor Melnyk, Matthew Riemer
2025	J	`jnl`	Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models. CoRR Pin-Yu Chen, Han Shen, Payel Das, Tianyi Chen
2025	J	`jnl`	GP-MoLFormer-Sim: Test Time Molecular Optimization through Contextual Similarity Guidance. CoRR Jirí Navrátil, Jarret Ross, Payel Das, Youssef Mroueh, Samuel C. Hoffman, Vijil Chenthamarakshan, Brian Belgodere
2025	A*	`conf`	Large Language Models can Become Strong Self-Detoxifiers. ICLR Ching-Yun Ko, Pin-Yu Chen, Payel Das, Youssef Mroueh, Soham Dan, Georgios Kollias, Subhajit Chaudhury, Tejaswini Pedapati, Luca Daniel
2025	—	`conf`	PEEL the Layers and Find Yourself: Revisiting Inference-Time Data Leakage for Residual Neural Networks. SaTML Huzaifa Arif, Keerthiram Murugesan, Payel Das, Alex Gittens, Pin-Yu Chen
2025	J	`jnl`	PEEL the Layers and Find Yourself: Revisiting Inference-time Data Leakage for Residual Neural Networks. CoRR Huzaifa Arif, Keerthiram Murugesan, Payel Das, Alex Gittens, Pin-Yu Chen
2025	J	`jnl`	Patching LLM Like Software: A Lightweight Method for Improving Safety Policy in Large Language Models. CoRR Huzaifa Arif, Keerthiram Murugesan, Ching-Yun Ko, Pin-Yu Chen, Payel Das, Alex Gittens
2025	—	`conf`	Position: Theory of Mind Benchmarks are Broken for Large Language Models. ICML (Position Papers) Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell
2025	A*	`conf`	SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection. ICLR Han Shen, Pin-Yu Chen, Payel Das, Tianyi Chen
2024	—	`conf`	A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques. ACL (1) Megh Thakkar, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
2024	J	`jnl`	A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques. CoRR Megh Thakkar, Quentin Fournier, Matthew D. Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
2024	J	`jnl`	Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units. J. Chem. Inf. Model. Hatem Helal, Jesun Firoz, Jenna A. Bilbrey, Henry Sprueill, Kristina M. Herman, Mario Michael Krell, Tom Murray, Manuel Lopez Roldan, Mike Kraus, Ang Li, Payel Das, Sotiris S. Xantheas, Sutanay Choudhury
2024	J	`jnl`	Anniversary AI reflections. Nat. Mac. Intell. Noelia Ferruz, Marinka Zitnik, Pierre-Yves Oudeyer, Emmie Hine, Nandana Sengupta, Yiyu Shi, Diana Mincu, Sebastian Porsdam Mann, Payel Das, Francesco Stella
2024	J	`jnl`	Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data. Trans. Mach. Learn. Res. Samuel C. Hoffman, Payel Das, Karthikeyan Shanmugam, Kahini Wadhawan, Prasanna Sattigeri
2024	A*	`conf`	Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints. ICML Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Dürholt, Payel Das, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic
2024	J	`jnl`	Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints. CoRR Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Dürholt, Payel Das, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic
2024	J	`jnl`	Can Large Language Models Adapt to Other Agents In-Context? CoRR Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell
2024	J	`jnl`	Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs. CoRR Megh Thakkar, Yash More, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
2024	J	`jnl`	GP-MoLFormer: A Foundation Model For Molecular Generation. CoRR Jerret Ross, Brian Belgodere, Samuel C. Hoffman, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
2024	J	`jnl`	Generation Constraint Scaling Can Mitigate Hallucination. CoRR Georgios Kollias, Payel Das, Subhajit Chaudhury
2024	J	`jnl`	Large Language Models can be Strong Self-Detoxifiers. CoRR Ching-Yun Ko, Pin-Yu Chen, Payel Das, Youssef Mroueh, Soham Dan, Georgios Kollias, Subhajit Chaudhury, Tejaswini Pedapati, Luca Daniel
2024	A*	`conf`	Larimar: Large Language Models with Episodic Memory Control. ICML Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarathkrishna Swaminathan, Sihui Dai, Aurélie C. Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jirí Navrátil, Soham Dan, Pin-Yu Chen
2024	J	`jnl`	Larimar: Large Language Models with Episodic Memory Control. CoRR Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarath Swaminathan, Sihui Dai, Aurélie C. Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jirí Navrátil, Soham Dan, Pin-Yu Chen
2024	J	`jnl`	Mapping Metaverse Research to the Sustainable Development Goal of Good Health and Well-Being. IEEE Access Raghu Raman, Laurie Hughes, Santanu Mandal, Payel Das, Prema Nedungadi
2024	A*	`conf`	Multi-Scale Representation Learning for Protein Fitness Prediction. NeurIPS Zuobai Zhang, Pascal Notin, Yining Huang, Aurélie C. Lozano, Vijil Chenthamarakshan, Debora S. Marks, Payel Das, Jian Tang
2024	J	`jnl`	Multi-Scale Representation Learning for Protein Fitness Prediction. CoRR Zuobai Zhang, Pascal Notin, Yining Huang, Aurélie C. Lozano, Vijil Chenthamarakshan, Debora S. Marks, Payel Das, Jian Tang
2024	J	`jnl`	Needle in the Haystack for Memory Based Large Language Models. CoRR Elliot Nelson, Georgios Kollias, Payel Das, Subhajit Chaudhury, Soham Dan
2024	—	`conf`	NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. ACL (Findings) Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurélie C. Lozano, Payel Das, Georgios Kollias
2024	J	`jnl`	NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. CoRR Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurélie C. Lozano, Payel Das, Georgios Kollias
2024	J	`jnl`	ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation. CoRR Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2024	J	`jnl`	SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection. CoRR Han Shen, Pin-Yu Chen, Payel Das, Tianyi Chen
2024	J	`jnl`	Structure-Informed Protein Language Model. CoRR Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2024	A*	`conf`	What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks. ICML Ching-Yun Ko, Pin-Yu Chen, Payel Das, Jeet Mohapatra, Luca Daniel
2023	J	`jnl`	A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. J. Chem. Inf. Model. Jack Scantlebury, Lucy Vost, Anna Carbery, Thomas E. Hadfield, Oliver M. Turnbull, Nathan Brown, Vijil Chenthamarakshan, Payel Das, Harold Grosjean, Frank von Delft, Charlotte M. Deane
2023	J	`jnl`	AI Maintenance: A Robustness Perspective. Computer Pin-Yu Chen, Payel Das
2023	J	`jnl`	AI Maintenance: A Robustness Perspective. CoRR Pin-Yu Chen, Payel Das
2023	Misc	`conf`	Direction Aware Positional and Structural Encoding for Directed Graph Neural Networks. ICASSP Yonas Sium, Georgios Kollias, Tsuyoshi Idé, Payel Das, Naoki Abe, Aurélie C. Lozano, Qi Li
2023	A*	`conf`	Efficient Equivariant Transfer Learning from Pretrained Models. NeurIPS Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Driggs-Campbell, Payel Das, Lav R. Varshney
2023	J	`jnl`	Enhancing Protein Language Models with Structure-based Encoder and Pre-training. CoRR Zuobai Zhang, Minghao Xu, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2023	A*	`conf`	Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. AAAI Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
2023	J	`jnl`	Equivariant Few-Shot Learning from Pretrained Models. CoRR Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Rose Driggs-Campbell, Payel Das, Lav R. Varshney
2023	A*	`conf`	Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction. ICML Minghao Guo, Veronika Thost, Samuel W. Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik
2023	J	`jnl`	Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction. CoRR Minghao Guo, Veronika Thost, Samuel W. Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik
2023	J	`jnl`	Keeping Up with the Language Models: Robustness-Bias Interplay in NLI Data and Models. CoRR Ioana Baldini, Chhavi Yadav, Payel Das, Kush R. Varshney
2023	J	`jnl`	Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction. CoRR Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
2023	J	`jnl`	Physics-enhanced deep surrogates for partial differential equations. Nat. Mac. Intell. Raphaël Pestourie, Youssef Mroueh, Chris Rackauckas, Payel Das, Steven G. Johnson
2023	A*	`conf`	Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction. NeurIPS Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
2023	A*	`conf`	Protein Representation Learning by Geometric Structure Pretraining. ICLR Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2023	A*	`conf`	Reprogramming Pretrained Language Models for Antibody Sequence Infilling. ICML Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das
2023	J	`jnl`	Reprogramming Pretrained Language Models for Protein Sequence Representation Learning. CoRR Ria Vinod, Pin-Yu Chen, Payel Das
2023	A*	`conf`	The Impact of Positional Encoding on Length Generalization in Transformers. NeurIPS Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Payel Das, Siva Reddy
2023	J	`jnl`	The Impact of Positional Encoding on Length Generalization in Transformers. CoRR Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Payel Das, Siva Reddy
2023	J	`jnl`	The incentive gap in data work in the era of large models. Nat. Mac. Intell. Katy Ilonka Gero, Payel Das, Pierre L. Dognin, Inkit Padhi, Prasanna Sattigeri, Kush R. Varshney
2022	J	`jnl`	Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework. CoRR Vijil Chenthamarakshan, Samuel C. Hoffman, C. David Owen, Petra Lukacik, Claire Strain-Damerell, Daren Fearon, Tika R. Malla, Anthony Tumber, Christopher J. Schofield, Helen M. E. Duyvesteyn, Wanwisa Dejnirattisai, Loic Carrique, Thomas S. Walter, Gavin R. Screaton, Tetiana Matviiuk, Aleksandra Mojsilovic, Jason Crain, Martin A. Walsh, David I. Stuart, Payel Das
2022	J	`jnl`	Active Sampling of Multiple Sources for Sequential Estimation. CoRR Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das
2022	J	`jnl`	Active Sampling of Multiple Sources for Sequential Estimation. IEEE Trans. Signal Process. Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das
2022	J	`jnl`	AlphaFold Distillation for Improved Inverse Protein Folding. CoRR Igor Melnyk, Aurélie C. Lozano, Payel Das, Vijil Chenthamarakshan
2022	Misc	`conf`	Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. ICASSP Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
2022	A*	`conf`	Biological Sequence Design with GFlowNets. ICML Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio
2022	J	`jnl`	Biological Sequence Design with GFlowNets. CoRR Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio
2022	J	`jnl`	Causal Graphs Underlying Generative Models: Path to Learning with Limited Data. CoRR Samuel C. Hoffman, Kahini Wadhawan, Payel Das, Prasanna Sattigeri, Karthikeyan Shanmugam
2022	—	`conf`	Cloud-Based Real-Time Molecular Screening Platform with MolFormer. ECML/PKDD (6) Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre L. Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young
2022	J	`jnl`	Cloud-Based Real-Time Molecular Screening Platform with MolFormer. CoRR Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre L. Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young
2022	J	`jnl`	Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions. CoRR Chanakya Ekbote, Moksh Jain, Payel Das, Yoshua Bengio
2022	A*	`conf`	Data-Efficient Graph Grammar Learning for Molecular Generation. ICLR Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik
2022	J	`jnl`	Data-Efficient Graph Grammar Learning for Molecular Generation. CoRR Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik
2022	J	`jnl`	Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. CoRR Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
2022	J	`jnl`	Explaining Artificial Intelligence Generation and Creativity: Human interpretability for novel ideas and artifacts. IEEE Signal Process. Mag. Payel Das, Lav R. Varshney
2022	A*	`conf`	Fourier Representations for Black-Box Optimization over Categorical Variables. AAAI Hamid Dadkhahi, Jesus Rios, Karthikeyan Shanmugam, Payel Das
2022	J	`jnl`	Fourier Representations for Black-Box Optimization over Categorical Variables. CoRR Hamid Dadkhahi, Jesus Rios, Karthikeyan Shanmugam, Payel Das
2022	J	`jnl`	GT4SD: Generative Toolkit for Scientific Discovery. CoRR Matteo Manica, Joris Cadow, Dimitrios Christofidellis, Ashish Dave, Jannis Born, Dean Clarke, Yves Gaetan Nana Teukam, Samuel C. Hoffman, Matthew Buchan, Vijil Chenthamarakshan, Timothy Donovan, Hsiang-Han Hsu, Federico Zipoli, Oliver Schilter, Giorgio Giannone, Akihiro Kishimoto, Lisa Hamada, Inkit Padhi, Karl Wehden, Lauren McHugh, Alexy Khrabrov, Payel Das, Seiji Takeda, John R. Smith
2022	—	`conf`	Knowledge Graph Generation From Text. EMNLP (Findings) Igor Melnyk, Pierre L. Dognin, Payel Das
2022	J	`jnl`	Knowledge Graph Generation From Text. CoRR Igor Melnyk, Pierre L. Dognin, Payel Das
2022	J	`jnl`	Large-scale chemical language representations capture molecular structure and properties. Nat. Mac. Intell. Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das
2022	J	`jnl`	Learning Geometrically Disentangled Representations of Protein Folding Simulations. CoRR N. Joseph Tatro, Payel Das, Pin-Yu Chen, Vijil Chenthamarakshan, Rongjie Lai
2022	J	`jnl`	Modified Galerkin method for Volterra-Fredholm-Hammerstein integral equations. Comput. Appl. Math. Payel Das, Kapil Kant, B. V. Ratish Kumar
2022	J	`jnl`	Optimizing molecules using efficient queries from property evaluations. Nat. Mach. Intell. Samuel C. Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das
2022	J	`jnl`	Protein Representation Learning by Geometric Structure Pretraining. CoRR Zuobai Zhang, Minghao Xu, Arian R. Jamasb, Vijil Chenthamarakshan, Aurélie C. Lozano, Payel Das, Jian Tang
2022	J	`jnl`	Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators. CoRR Jenna A. Bilbrey, Kristina M. Herman, Henry Sprueill, Sotiris S. Xantheas, Payel Das, Manuel Lopez Roldan, Mike Kraus, Hatem Helal, Sutanay Choudhury
2022	J	`jnl`	Reprogramming Large Pretrained Language Models for Antibody Sequence Infilling. CoRR Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das
2022	J	`jnl`	SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data. CoRR Ching-Yun Ko, Pin-Yu Chen, Jeet Mohapatra, Payel Das, Luca Daniel
2022	A*	`conf`	Towards Creativity Characterization of Generative Models via Group-Based Subset Scanning. IJCAI Celia Cintas, Payel Das, Brian Quanz, Girmaw Abebe Tadesse, Skyler Speakman, Pin-Yu Chen
2022	J	`jnl`	Towards Creativity Characterization of Generative Models via Group-based Subset Scanning. CoRR Celia Cintas, Payel Das, Brian Quanz, Girmaw Abebe Tadesse, Skyler Speakman, Pin-Yu Chen
2021	B	`conf`	Active Binary Classification of Random Fields. ISIT Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das
2021	Misc	`conf`	Active Estimation From Multimodal Data. ICASSP Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das
2021	J	`jnl`	Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. CoRR Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
2021	J	`jnl`	Benchmarking deep generative models for diverse antibody sequence design. CoRR Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurélie C. Lozano
2021	A*	`conf`	Best Arm Identification in Contaminated Stochastic Bandits. NeurIPS Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das
2021	J	`jnl`	Do Large Scale Molecular Language Representations Capture Important Structural Information? CoRR Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das
2021	A*	`conf`	Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design. ICML Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
2021	J	`jnl`	Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design. CoRR Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
2021	J	`jnl`	Gi and Pal Scores: Deep Neural Network Generalization Statistics. CoRR Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen
2021	J	`jnl`	Mean-based Best Arm Identification in Stochastic Bandits under Reward Contamination. CoRR Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das
2021	J	`jnl`	Physics-enhanced deep surrogates for PDEs. CoRR Raphaël Pestourie, Youssef Mroueh, Chris Rackauckas, Payel Das, Steven G. Johnson
2021	A*	`conf`	Predicting Deep Neural Network Generalization with Perturbation Response Curves. NeurIPS Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen
2021	J	`jnl`	Predicting Deep Neural Network Generalization with Perturbation Response Curves. CoRR Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen
2021	—	`conf`	ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language Models. EMNLP (1) Pierre L. Dognin, Inkit Padhi, Igor Melnyk, Payel Das
2021	J	`jnl`	ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language Models. CoRR Pierre L. Dognin, Inkit Padhi, Igor Melnyk, Payel Das
2021	J	`jnl`	Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model. CoRR Samuel C. Hoffman, Vijil Chenthamarakshan, Dmitry Yu. Zubarev, Daniel P. Sanders, Payel Das
2021	A*	`conf`	Self-Progressing Robust Training. AAAI Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das
2021	J	`jnl`	Towards Interpreting Zoonotic Potential of Betacoronavirus Sequences With Attention. CoRR Kahini Wadhawan, Payel Das, Barbara A. Han, Ilya R. Fischhoff, Adrian C. Castellanos, Arvind Varsani, Kush R. Varshney
2021	J	`jnl`	Towards creativity characterization of generative models via group-based subset scanning. CoRR Celia Cintas, Payel Das, Brian Quanz, Skyler Speakman, Victor Akinwande, Pin-Yu Chen
2020	A*	`conf`	A Decentralized Parallel Algorithm for Training Generative Adversarial Nets. NeurIPS Mingrui Liu, Wei Zhang, Youssef Mroueh, Xiaodong Cui, Jarret Ross, Tianbao Yang, Payel Das
2020	J	`jnl`	Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics. CoRR Payel Das, Tom Sercu, Kahini Wadhawan, Inkit Padhi, Sebastian Gehrmann, Flaviu S. Cipcigan, Vijil Chenthamarakshan, Hendrik Strobelt, Cícero Nogueira dos Santos, Pin-Yu Chen, Yi Yan Yang, Jeremy Tan, James Hedrick, Jason Crain, Aleksandra Mojsilovic
2020	J	`jnl`	Active learning of deep surrogates for PDEs: Application to metasurface design. CoRR Raphaël Pestourie, Youssef Mroueh, Thanh V. Nguyen, Payel Das, Steven G. Johnson
2020	A*	`conf`	Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness. ICLR Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin
2020	J	`jnl`	Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness. CoRR Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin
2020	J	`jnl`	Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics. CoRR Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das
2020	A*	`conf`	CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. NeurIPS Vijil Chenthamarakshan, Payel Das, Samuel C. Hoffman, Hendrik Strobelt, Inkit Padhi, Kar Wai Lim, Benjamin Hoover, Matteo Manica, Jannis Born, Teodoro Laino, Aleksandra Mojsilovic
2020	A*	`conf`	Combinatorial Black-Box Optimization with Expert Advice. KDD Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel C. Hoffman, Troy David Loeffler, Subramanian Sankaranarayanan
2020	J	`jnl`	Combinatorial Black-Box Optimization with Expert Advice. CoRR Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel C. Hoffman, Troy David Loeffler, Subramanian Sankaranarayanan
2020	—	`conf`	DualTKB: A Dual Learning Bridge between Text and Knowledge Base. EMNLP (1) Pierre L. Dognin, Igor Melnyk, Inkit Padhi, Cícero Nogueira dos Santos, Payel Das
2020	J	`jnl`	DualTKB: A Dual Learning Bridge between Text and Knowledge Base. CoRR Pierre L. Dognin, Igor Melnyk, Inkit Padhi, Cícero Nogueira dos Santos, Payel Das
2020	J	`jnl`	Explaining Chemical Toxicity using Missing Features. CoRR Kar Wai Lim, Bhanushee Sharma, Payel Das, Vijil Chenthamarakshan, Jonathan S. Dordick
2020	Misc	`conf`	Improving Efficiency in Large-Scale Decentralized Distributed Training. ICASSP Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David S. Kung, Michael Picheny
2020	J	`jnl`	Improving Efficiency in Large-Scale Decentralized Distributed Training. CoRR Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David S. Kung, Michael Picheny
2020	A*	`conf`	Learning Implicit Text Generation via Feature Matching. ACL Inkit Padhi, Pierre L. Dognin, Ke Bai, Cícero Nogueira dos Santos, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
2020	J	`jnl`	Learning Implicit Text Generation via Feature Matching. CoRR Inkit Padhi, Pierre L. Dognin, Ke Bai, Cícero Nogueira dos Santos, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
2020	A*	`conf`	Optimizing Mode Connectivity via Neuron Alignment. NeurIPS N. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri, Rongjie Lai
2020	J	`jnl`	Optimizing Mode Connectivity via Neuron Alignment. CoRR N. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri, Rongjie Lai
2020	J	`jnl`	Optimizing Molecules using Efficient Queries from Property Evaluations. CoRR Samuel C. Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das
2020	J	`jnl`	Reprogramming Language Models for Molecular Representation Learning. CoRR Ria Vinod, Pin-Yu Chen, Payel Das
2020	J	`jnl`	Self-Progressing Robust Training. CoRR Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das
2020	J	`jnl`	Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. CoRR Vijil Chenthamarakshan, Payel Das, Inkit Padhi, Hendrik Strobelt, Kar Wai Lim, Benjamin Hoover, Samuel C. Hoffman, Aleksandra Mojsilovic
2020	A*	`conf`	Toward a neuro-inspired creative decoder. IJCAI Payel Das, Brian Quanz, Pin-Yu Chen, Jae-wook Ahn, Dhruv Shah
2020	A*	`conf`	Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets. ICLR Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui, Payel Das, Tianbao Yang
2019	J	`jnl`	Decentralized Parallel Algorithm for Training Generative Adversarial Nets. CoRR Mingrui Liu, Youssef Mroueh, Wei Zhang, Xiaodong Cui, Jerret Ross, Tianbao Yang, Payel Das
2019	—	`conf`	Interactive Visual Exploration of Latent Space (IVELS) for peptide auto-encoder model selection. DGS@ICLR Tom Sercu, Sebastian Gehrmann, Hendrik Strobelt, Payel Das, Inkit Padhi, Cícero Nogueira dos Santos, Kahini Wadhawan, Vijil Chenthamarakshan
2019	J	`jnl`	Projection and multi projection methods for nonlinear integral equations on the half-line. J. Comput. Appl. Math. Nilofar Nahid, Payel Das, Gnaneshwar Nelakanti
2019	—	`conf`	Superconvergence of Iterated Galerkin Method for a Class of Nonlinear Fredholm Integral Equations. ICITAM Payel Das, Nilofar Nahid, Gnaneshwar Nelakanti
2019	J	`jnl`	Toward A Neuro-inspired Creative Decoder. CoRR Payel Das, Brian Quanz, Pin-Yu Chen, Jae-wook Ahn
2019	J	`jnl`	Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets. CoRR Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui, Payel Das, Tianbao Yang
2018	J	`jnl`	Discrete Legendre spectral Galerkin method for Urysohn integral equations. Int. J. Comput. Math. Payel Das, Gnaneshwar Nelakanti, Guangqing Long
2018	A*	`conf`	Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives. NeurIPS Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Pai-Shun Ting, Karthikeyan Shanmugam, Payel Das
2018	J	`jnl`	Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives. CoRR Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Pai-Shun Ting, Karthikeyan Shanmugam, Payel Das
2018	J	`jnl`	PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences. CoRR Payel Das, Kahini Wadhawan, Oscar Chang, Tom Sercu, Cícero Nogueira dos Santos, Matthew Riemer, Inkit Padhi, Vijil Chenthamarakshan, Aleksandra Mojsilovic
2017	—	`conf`	Automated brain state identification using graph embedding. PRNI Hongyuan You, Adam Liska, Nathan Russell, Payel Das
2017	J	`jnl`	Neurology-as-a-Service for the Developing World. CoRR Tejas Dharamsi, Payel Das, Tejaswini Pedapati, Gregory Bramble, Vinod Muthusamy, Horst Samulowitz, Kush R. Varshney, Yuvaraj Rajamanickam, John Thomas, Justin Dauwels
2016	J	`jnl`	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. Payel Das, Gnaneshwar Nelakanti
2016	J	`jnl`	Erratum to: Discrete Legendre spectral projection methods for Fredholm-Hammerstein integral equations [J. Comput. Appl. Math 278 (2015) 293-305]. J. Comput. Appl. Math. Payel Das, Gnaneshwar Nelakanti, Guangqing Long
2016	J	`jnl`	Legendre Spectral Projection Methods for Fredholm-Hammerstein Integral Equations. J. Sci. Comput. Payel Das, Mitali Madhumita Sahani, Gnaneshwar Nelakanti, Guangqing Long
2015	J	`jnl`	Convergence analysis of discrete legendre spectral projection methods for hammerstein integral equations of mixed type. Appl. Math. Comput. Payel Das, Gnaneshwar Nelakanti
2015	J	`jnl`	Discrete Legendre spectral projection methods for Fredholm-Hammerstein integral equations. J. Comput. Appl. Math. Payel Das, Gnaneshwar Nelakanti, Guangqing Long
2014	J	`jnl`	Comparative study of metamodelling techniques in building energy simulation: Guidelines for practitioners. Simul. Model. Pract. Theory Liesje Van Gelder, Payel Das, Hans Janssen, Staf Roels
2014	J	`jnl`	Legendre spectral projection methods for Urysohn integral equations. J. Comput. Appl. Math. Payel Das, Mitali Madhumita Sahani, Gnaneshwar Nelakanti
2011	J	`jnl`	Modeling mutations of influenza virus with IBM Blue Gene. IBM J. Res. Dev. Zhen Xia, Payel Das, Tien Huynh, Ajay K. Royyuru, Ruhong Zhou
2009	J	`jnl`	Free energy simulations reveal a double mutant avian H5N1 virus hemagglutinin with altered receptor binding specificity. J. Comput. Chem. Payel Das, Jingyuan Li, Ajay K. Royyuru, Ruhong Zhou
2006	J	`jnl`	Low-dimensional, free-energy landscapes of protein-folding reactions by nonlinear dimensionality reduction. Proc. Natl. Acad. Sci. USA Payel Das, Mark Moll, Hernán Stamati, Lydia E. Kavraki, Cecilia Clementi