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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

* 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

* 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

* 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

* 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

* 24 pages, 9 figures, code available at 

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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

* 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

* 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

* 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

* 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

* 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

* 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

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

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