Publications

This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.

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20 results for Samuel Hoffman

Learning to Optimize Molecules with a Chemical Language Model
- - Jerret Ross
  - Samuel Hoffman
  - et al.
- 2024
- NeurIPS 2024
AI Explainability 360: Impact and Design
- - Vijay Arya
  - Rachel K. E. Bellamy
  - et al.
- 2022
- IAAI 2022
AI Explainability 360 Toolkit
- - Vijay Arya
  - Rachel Bellamy
  - et al.
- 2021
- CODS-COMAD 2021
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations
- - Yair Schiff
  - Vijil Chenthamarakshan
  - et al.
- 2022
- ICASSP 2022
Combinatorial Black-Box Optimization with Expert Advice
- - Hamid Dadkhahi
  - Karthikeyan Shanmugam
  - et al.
- 2020
- KDD 2020
One Explanation Does Not Fit All: A Toolkit And Taxonomy Of AI Explainability Techniques
- - Vijay Arya
  - Rachel K. Bellamy
  - et al.
- 2021
- INFORMS 2021
Ai explainability 360: An extensible toolkit for understanding data and machine learning models
- - Vijay Arya
  - Rachel Bellamy
  - et al.
- 2020
- JMLR
Fairness GAN: Generating datasets with fairness properties using a generative adversarial network
- - Prasanna Sattigeri
  - Samuel C. Hoffman
  - et al.
- 2019
- IBM J. Res. Dev
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias
- - Rachel Bellamy
  - Aleksandra Mojsilovic
  - et al.
- 2019
- IBM J. Res. Dev
Think Your Artificial Intelligence Software Is Fair? Think Again
- - Rachel Bellamy
  - Kuntal Dey
  - et al.
- 2019
- IEEE Software