AI Fairness 360: An extensible toolkit for detecting, understanding, and mitigating unwanted algorithmic bias RKE Bellamy, K Dey, M Hind, SC Hoffman, S Houde, K Kannan, P Lohia, ... arXiv preprint arXiv:1810.01943, 2018 | 539 | 2018 |
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias RKE Bellamy, K Dey, M Hind, SC Hoffman, S Houde, K Kannan, P Lohia, ... IBM Journal of Research and Development 63 (4/5), 4: 1-4: 15, 2019 | 335 | 2019 |
One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ... arXiv preprint arXiv:1909.03012, 2019 | 261 | 2019 |
Fairness GAN: Generating datasets with fairness properties using a generative adversarial network P Sattigeri, SC Hoffman, V Chenthamarakshan, KR Varshney IBM Journal of Research and Development 63 (4/5), 3: 1-3: 9, 2019 | 146* | 2019 |
CogMol: Target-specific and selective drug design for COVID-19 using deep generative models V Chenthamarakshan, P Das, S Hoffman, H Strobelt, I Padhi, KW Lim, ... Advances in Neural Information Processing Systems 33, 4320-4332, 2020 | 70 | 2020 |
AI Explainability 360 Toolkit V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ... Proceedings of the 3rd ACM India Joint International Conference on Data …, 2021 | 54 | 2021 |
One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques. arXiv 2019 V Arya, RK Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ... arXiv preprint arXiv:1909.03012, 2022 | 44 | 2022 |
Think your artificial intelligence software is fair? Think again RKE Bellamy, K Dey, M Hind, SC Hoffman, S Houde, K Kannan, P Lohia, ... IEEE Software 36 (4), 76-80, 2019 | 32 | 2019 |
AI Fairness 360: An Extensible Toolkit for Detecting RKE Bellamy, K Dey, M Hind, SC Hoffman, S Houde, K Kannan, P Lohia, ... Understanding, and Mitigating Unwanted Algorithmic Bias, 2018 | 29 | 2018 |
Optimizing molecules using efficient queries from property evaluations SC Hoffman, V Chenthamarakshan, K Wadhawan, PY Chen, P Das Nature Machine Intelligence 4 (1), 21-31, 2022 | 24 | 2022 |
Combinatorial black-box optimization with expert advice H Dadkhahi, K Shanmugam, J Rios, P Das, SC Hoffman, TD Loeffler, ... Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 7 | 2020 |
AI explainability 360: hands-on tutorial V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ... Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020 | 6 | 2020 |
GT4SD: Generative Toolkit for Scientific Discovery M Manica, J Cadow, D Christofidellis, A Dave, J Born, D Clarke, ... arXiv preprint arXiv:2207.03928, 2022 | 3 | 2022 |
Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model SC Hoffman, V Chenthamarakshan, DY Zubarev, DP Sanders, P Das arXiv preprint arXiv:2112.01625, 2021 | 3 | 2021 |
Augmenting molecular deep generative models with topological data analysis representations Y Schiff, V Chenthamarakshan, SC Hoffman, KN Ramamurthy, P Das ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 2 | 2022 |
An empirical study of modular bias mitigators and ensembles M Feffer, M Hirzel, SC Hoffman, K Kate, P Ram, A Shinnar arXiv preprint arXiv:2202.00751, 2022 | 2 | 2022 |
Artificial intelligence certification of factsheets using blockchain K Kannan, PK Lohia, S Hoffman, KR Varshney, S Mehta US Patent 11,483,154, 2022 | 1 | 2022 |
Causal Graphs Underlying Generative Models: Path to Learning with Limited Data SC Hoffman, K Wadhawan, P Das, P Sattigeri, K Shanmugam arXiv preprint arXiv:2207.07174, 2022 | 1 | 2022 |
Deep surrogate langevin sampling for multi-objective constraint black box optimization with applications to optimal inverse design problems T Van Nguyen, Y Mroueh, SC Hoffman, P Das, PL Dognin, G Romano, ... US Patent App. 17/008,197, 2022 | 1 | 2022 |
Continuity report: Revisiting grocery recognition using tensorflow SC Hoffman, D Thiagarajan | 1 | |