Alert button
Picture for Samuel C. Hoffman

Samuel C. Hoffman

Alert button

Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions

Feb 17, 2023
Manish Nagireddy, Moninder Singh, Samuel C. Hoffman, Evaline Ju, Karthikeyan Natesan Ramamurthy, Kush R. Varshney

Figure 1 for Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions
Figure 2 for Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions
Figure 3 for Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions
Figure 4 for Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions
Viaarxiv icon

Navigating Ensemble Configurations for Algorithmic Fairness

Oct 11, 2022
Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar

Figure 1 for Navigating Ensemble Configurations for Algorithmic Fairness
Figure 2 for Navigating Ensemble Configurations for Algorithmic Fairness
Figure 3 for Navigating Ensemble Configurations for Algorithmic Fairness
Figure 4 for Navigating Ensemble Configurations for Algorithmic Fairness
Viaarxiv icon

Causal Graphs Underlying Generative Models: Path to Learning with Limited Data

Jul 14, 2022
Samuel C. Hoffman, Kahini Wadhawan, Payel Das, Prasanna Sattigeri, Karthikeyan Shanmugam

Figure 1 for Causal Graphs Underlying Generative Models: Path to Learning with Limited Data
Figure 2 for Causal Graphs Underlying Generative Models: Path to Learning with Limited Data
Figure 3 for Causal Graphs Underlying Generative Models: Path to Learning with Limited Data
Figure 4 for Causal Graphs Underlying Generative Models: Path to Learning with Limited Data
Viaarxiv icon

GT4SD: Generative Toolkit for Scientific Discovery

Jul 08, 2022
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

Figure 1 for GT4SD: Generative Toolkit for Scientific Discovery
Figure 2 for GT4SD: Generative Toolkit for Scientific Discovery
Figure 3 for GT4SD: Generative Toolkit for Scientific Discovery
Viaarxiv icon

Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework

Apr 19, 2022
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

Figure 1 for Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework
Figure 2 for Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework
Figure 3 for Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework
Figure 4 for Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework
Viaarxiv icon

An Empirical Study of Modular Bias Mitigators and Ensembles

Feb 01, 2022
Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar

Figure 1 for An Empirical Study of Modular Bias Mitigators and Ensembles
Figure 2 for An Empirical Study of Modular Bias Mitigators and Ensembles
Figure 3 for An Empirical Study of Modular Bias Mitigators and Ensembles
Figure 4 for An Empirical Study of Modular Bias Mitigators and Ensembles
Viaarxiv icon

Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model

Dec 02, 2021
Samuel C. Hoffman, Vijil Chenthamarakshan, Dmitry Yu. Zubarev, Daniel P. Sanders, Payel Das

Figure 1 for Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model
Figure 2 for Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model
Figure 3 for Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model
Figure 4 for Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model
Viaarxiv icon

AI Explainability 360: Impact and Design

Sep 24, 2021
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 Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

Figure 1 for AI Explainability 360: Impact and Design
Figure 2 for AI Explainability 360: Impact and Design
Figure 3 for AI Explainability 360: Impact and Design
Figure 4 for AI Explainability 360: Impact and Design
Viaarxiv icon

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

Figure 1 for Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
Figure 2 for Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
Figure 3 for Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
Figure 4 for Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
Viaarxiv icon

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

Sep 14, 2019
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 Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

Figure 1 for One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Figure 2 for One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Figure 3 for One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Figure 4 for One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Viaarxiv icon