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Payel Das

Predicting Deep Neural Network Generalization with Perturbation Response Curves


Jun 09, 2021
Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen

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* arXiv admin note: substantial text overlap with arXiv:2104.03469 
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Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations


Jun 08, 2021
Yair Schiff, Vijil Chenthamarakshan, Samuel Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das

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Gi and Pal Scores: Deep Neural Network Generalization Statistics


Apr 08, 2021
Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen

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* Accepted to RobustML Workshop at ICLR 2021 
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Towards creativity characterization of generative models via group-based subset scanning


Apr 01, 2021
Celia Cintas, Payel Das, Brian Quanz, Skyler Speakman, Victor Akinwande, Pin-Yu Chen

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* Synthetic Data Generation Workshop at ICLR'21 
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Reprogramming Language Models for Molecular Representation Learning


Jan 06, 2021
Ria Vinod, Pin-Yu Chen, Payel Das

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* 6 pages, 5 tables, accepted at Learning Meaningful Representations of Life @ NeurIPS 2020, Women in Machine Learning @ NeurIPS 2020. 8 pages, LaTeX; typos corrected, references added 
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Self-Progressing Robust Training


Dec 22, 2020
Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das

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* Accepted in AAAI2021 
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Optimizing Molecules using Efficient Queries from Property Evaluations


Nov 03, 2020
Samuel Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das

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DualTKB: A Dual Learning Bridge between Text and Knowledge Base


Oct 27, 2020
Pierre L. Dognin, Igor Melnyk, Inkit Padhi, Cicero Nogueira dos Santos, Payel Das

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* Equal Contributions of Authors Pierre L. Dognin, Igor Melnyk, and Inkit Padhi. Accepted at EMNLP'20 
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Characterizing the Latent Space of Molecular Deep Generative Models with Persistent Homology Metrics


Oct 18, 2020
Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das

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Explaining Chemical Toxicity using Missing Features


Sep 23, 2020
Kar Wai Lim, Bhanushee Sharma, Payel Das, Vijil Chenthamarakshan, Jonathan S. Dordick

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Optimizing Mode Connectivity via Neuron Alignment


Sep 05, 2020
N. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri, Rongjie Lai

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* 24 pages, 9 figures, code available at https://github.com/IBM/NeuronAlignment 
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Active learning of deep surrogates for PDEs: Application to metasurface design


Aug 24, 2020
Raphaël Pestourie, Youssef Mroueh, Thanh V. Nguyen, Payel Das, Steven G. Johnson

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* submitted to npj 
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Combinatorial Black-Box Optimization with Expert Advice


Jun 06, 2020
Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel Hoffman, Troy David Loeffler, Subramanian Sankaranarayanan

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Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics


May 22, 2020
Payel Das, Tom Sercu, Kahini Wadhawan, Inkit Padhi, Sebastian Gehrmann, Flaviu Cipcigan, Vijil Chenthamarakshan, Hendrik Strobelt, Cicero dos Santos, Pin-Yu Chen, Yi Yan Yang, Jeremy Tan, James Hedrick, Jason Crain, Aleksandra Mojsilovic

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Learning Implicit Text Generation via Feature Matching


May 09, 2020
Inkit Padhi, Pierre Dognin, Ke Bai, Cicero Nogueira dos Santos, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das

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* ACL 2020 
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Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness


Apr 30, 2020
Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin

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* accepted by ICLR 2020 
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Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models


Apr 02, 2020
Vijil Chenthamarakshan, Payel Das, Inkit Padhi, Hendrik Strobelt, Kar Wai Lim, Ben Hoover, Samuel C. Hoffman, Aleksandra Mojsilovic

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Improving Efficiency in Large-Scale Decentralized Distributed Training


Feb 04, 2020
Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David Kung, Michael Picheny

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* 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP'2020) Oral 
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Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets


Dec 26, 2019
Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui, Payel Das, Tianbao Yang

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* Accepted by ICLR 2020 
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Decentralized Parallel Algorithm for Training Generative Adversarial Nets


Oct 30, 2019
Mingrui Liu, Youssef Mroueh, Wei Zhang, Xiaodong Cui, Jerret Ross, Tianbao Yang, Payel Das

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* Accepted by NeurIPS Smooth Games Optimization and Machine Learning Workshop: bridging game theory and deep learning, 2019 
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Toward A Neuro-inspired Creative Decoder


Feb 09, 2019
Payel Das, Brian Quanz, Pin-Yu Chen, Jae-wook Ahn

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Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives


Oct 29, 2018
Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Paishun Ting, Karthikeyan Shanmugam, Payel Das

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PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences


Oct 22, 2018
Payel Das, Kahini Wadhawan, Oscar Chang, Tom Sercu, Cicero Dos Santos, Matthew Riemer, Inkit Padhi, Vijil Chenthamarakshan, Aleksandra Mojsilovic

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Autism Classification Using Brain Functional Connectivity Dynamics and Machine Learning


Dec 21, 2017
Ravi Tejwani, Adam Liska, Hongyuan You, Jenna Reinen, Payel Das

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Neurology-as-a-Service for the Developing World


Nov 22, 2017
Tejas Dharamsi, Payel Das, Tejaswini Pedapati, Gregory Bramble, Vinod Muthusamy, Horst Samulowitz, Kush R. Varshney, Yuvaraj Rajamanickam, John Thomas, Justin Dauwels

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* Presented at NIPS 2017 Workshop on Machine Learning for the Developing World 
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