| Fairness definitions explained S Verma, J Rubin 2018 IEEE/ACM International Workshop on Software Fairness (FairWare), 1-7, 2018 | 1496 | 2018 |
| Counterfactual explanations for machine learning: A review S Verma, J Dickerson, K Hines arXiv preprint arXiv:2010.10596, 2020 | 798* | 2020 |
| Counterfactual Explanations for Machine Learning: Challenges Revisited S Verma, J Dickerson, K Hines arXiv preprint arXiv:2106.07756, 2021 | 47 | 2021 |
| Amortized Generation of Sequential Algorithmic Recourses for Black-box Models S Verma, K Hines, JP Dickerson AAAI 2022, 2022 | 42* | 2022 |
| Removing biased data to improve fairness and accuracy S Verma, M Ernst, R Just arXiv preprint arXiv:2102.03054, 2021 | 32 | 2021 |
| Synergistic debug-repair of heap manipulations S Verma, S Roy Proceedings of the 2017 11th Joint Meeting on Foundations of Software …, 2017 | 30 | 2017 |
| Facets of fairness in search and recommendation S Verma, R Gao, C Shah Bias and Social Aspects in Search and Recommendation: First International …, 2020 | 22 | 2020 |
| Shapeflow: Dynamic shape interpreter for tensorflow S Verma, Z Su arXiv preprint arXiv:2011.13452, 2020 | 16 | 2020 |
| Pitfalls of explainable ML: an industry perspective S Verma, A Lahiri, JP Dickerson, SI Lee arXiv preprint arXiv:2106.07758, 2021 | 14 | 2021 |
| Debug-localize-repair: a symbiotic construction for heap manipulations S Verma, S Roy Formal Methods in System Design 58 (3), 399-439, 2021 | 10 | 2021 |
| Recxplainer: post-hoc attribute-based explanations for recommender systems S Verma, A Beniwal, N Sadagopan, A Seshadri | 4 | 2022 |
| RecRec: Algorithmic Recourse for Recommender Systems S Verma, A Singh, V Boonsanong, JP Dickerson, C Shah Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 3 | 2023 |
| Benchmarking symbolic execution using constraint problems-initial results S Verma, RHC Yap 2019 IEEE 31st International Conference on Tools with Artificial …, 2019 | 3 | 2019 |
| Effective backdoor mitigation depends on the pre-training objective S Verma, G Bhatt, A Schwarzschild, S Singhal, AM Das, C Shah, ... arXiv preprint arXiv:2311.14948, 2023 | 2 | 2023 |
| Methods and apparatus for generating fast counterfactual explanations for black-box models using reinforcement learning (Patent) S Verma, J Dickerson, K Hines US Patent 11,403,538, 2022 | 2 | 2022 |
| How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold S Verma, R Rassin, A Das, G Bhatt, P Seshadri, C Shah, J Bilmes, ... arXiv preprint arXiv:2410.15002, 2024 | 1 | 2024 |
| NAP: Noise-Based Sensitivity Analysis for Programs J Michel*, S Verma*, B Sherman, M Carbin WAX 2019, 2019 | | 2019 |
John P. DickersonAssociate Professor of Computer Science, University of Maryland & Chief Scientist, Arthur AIכתובת אימייל מאומתת בדומיין cs.umd.edu