Samuel C. Hoffman | DeepAI

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∙ 02/17/2023

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

Ensuring trustworthiness in machine learning (ML) models is a multi-dime...

0 Manish Nagireddy, et al. ∙

∙ 10/11/2022

Navigating Ensemble Configurations for Algorithmic Fairness

Bias mitigators can improve algorithmic fairness in machine learning mod...

0 Michael Feffer, et al. ∙

∙ 07/14/2022

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

Training generative models that capture rich semantics of the data and i...

4 Samuel C. Hoffman, et al. ∙

∙ 07/08/2022

GT4SD: Generative Toolkit for Scientific Discovery

With the growing availability of data within various scientific domains,...

25 Matteo Manica, et al. ∙

∙ 04/19/2022

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

The COVID-19 pandemic has highlighted the urgency for developing more ef...

14 Vijil Chenthamarakshan, et al. ∙

∙ 02/01/2022

An Empirical Study of Modular Bias Mitigators and Ensembles

There are several bias mitigators that can reduce algorithmic bias in ma...

0 Michael Feffer, et al. ∙

∙ 12/02/2021

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

Photo-acid generators (PAGs) are compounds that release acids (H^+ ions)...

3 Samuel C. Hoffman, et al. ∙

∙ 09/24/2021

AI Explainability 360: Impact and Design

As artificial intelligence and machine learning algorithms become increa...

46 Vijay Arya, et al. ∙

∙ 04/02/2020

Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models

The recent COVID-19 pandemic has highlighted the need for rapid therapeu...

24 Vijil Chenthamarakshan, et al. ∙

∙ 09/06/2019

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

As artificial intelligence and machine learning algorithms make further ...

36 Vijay Arya, et al. ∙

∙ 10/03/2018

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Fairness is an increasingly important concern as machine learning models...

12 Rachel K. E. Bellamy, et al. ∙

∙ 05/24/2018

Fairness GAN

In this paper, we introduce the Fairness GAN, an approach for generating...

0 Prasanna Sattigeri, et al. ∙

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