Hoffman, Samuel C.

5 publications

TMLR 2024 Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data Samuel C Hoffman, Payel Das, Karthikeyan Shanmugam, Kahini Wadhawan, Prasanna Sattigeri

AutoML 2023 Searching for Fairer Machine Learning Ensembles Michael Feffer, Martin Hirzel, Samuel C Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar

AAAI 2022 AI Explainability 360: Impact and Design Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

NeurIPSW 2021 Sample-Efficient Generation of Novel Photo-Acid Generator Molecules Using a Deep Generative Model Samuel C Hoffman, Vijil Chenthamarakshan, Dmitry Zubarev, Daniel P Sanders, Payel Das

MLOSS 2020 AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang