Samuel C. Hoffman

31 papers A* 4Misc 1Journal 23Unranked 3
YearRankTypeTitle / 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
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
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 J jnl
GP-MoLFormer: A Foundation Model For Molecular Generation.
CoRR
Jerret Ross, Brian Belgodere, Samuel C. Hoffman, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das
2023 J jnl
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions.
CoRR
Manish Nagireddy, Moninder Singh, Samuel C. Hoffman, Evaline Ju, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
2023 — conf
Searching for Fairer Machine Learning Ensembles.
AutoML
Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar
2022 A* conf
AI Explainability 360: Impact and Design.
AAAI
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
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
An Empirical Study of Modular Bias Mitigators and Ensembles.
CoRR
Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar
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 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 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 J jnl
Navigating Ensemble Configurations for Algorithmic Fairness.
CoRR
Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar
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
2021 — conf
AI Explainability 360 Toolkit.
COMAD/CODS
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
2021 J jnl
AI Explainability 360: Impact and Design.
CoRR
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
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
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
2020 J jnl
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models.
J. Mach. Learn. Res.
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
2020 — conf
AI explainability 360: hands-on tutorial.
FAT*
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
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 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
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
2019 J jnl
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias.
IBM J. Res. Dev.
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
2019 J jnl
Fairness GAN: Generating datasets with fairness properties using a generative adversarial network.
IBM J. Res. Dev.
Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney
2019 J jnl
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.
CoRR
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
2019 J jnl
Think Your Artificial Intelligence Software Is Fair? Think Again.
IEEE Softw.
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
2018 J jnl
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias.
CoRR
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
2018 J jnl
Fairness GAN.
CoRR
Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney