| Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening DB Larremore, B Wilder, E Lester, S Shehata, JM Burke, JA Hay, ... Science advances 7 (1), eabd5393, 2021 | 912 | 2021 |
| Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization B Wilder, B Dilkina, M Tambe Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1658-1665, 2019 | 195 | 2019 |
| SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver PW Wang, PL Donti, B Wilder, Z Kolter International Conference on Machine Learning, 2019 | 183 | 2019 |
| Learning to complement humans B Wilder, E Horvitz, E Kamar International Joint Conference on Artificial Intelligence, 2020 | 114 | 2020 |
| Mipaal: Mixed integer program as a layer A Ferber, B Wilder, B Dilkina, M Tambe Proceedings of the AAAI Conference on Artificial Intelligence 34 (02), 1504-1511, 2020 | 95 | 2020 |
| Group-fairness in influence maximization A Tsang, B Wilder, E Rice, M Tambe, Y Zick International Joint Conference on Artificial Intelligence, 2019 | 89 | 2019 |
| End-to-end constrained optimization learning: A survey J Kotary, F Fioretto, P Van Hentenryck, B Wilder arXiv preprint arXiv:2103.16378, 2021 | 86 | 2021 |
| End to end learning and optimization on graphs B Wilder, E Ewing, B Dilkina, M Tambe Advances in Neural Information Processing Systems, 2019 | 67 | 2019 |
| Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City B Wilder, M Charpignon, JA Killian, HC Ou, A Mate, S Jabbari, A Perrault, ... Proceedings of the National Academy of Sciences 117 (41), 25904-25910, 2020 | 65 | 2020 |
| Controlling elections through social influence B Wilder, Y Vorobeychik International Conference on Autonomous Agents and Multiagent Systems, 2017 | 64 | 2017 |
| Influence maximization in the field: The arduous journey from emerging to deployed application A Yadav, B Wilder, E Rice, R Petering, J Craddock, A Yoshioka-Maxwell, ... Proceedings of the 16th conference on autonomous agents and multiagent …, 2017 | 61 | 2017 |
| Maximizing influence in an unknown social network B Wilder, N Immorlica, E Rice, M Tambe AAAI Conference on Artificial Intelligence, 2018 | 60 | 2018 |
| Uncharted but not Uninfluenced: Influence Maximization with an Uncertain Network. B Wilder, A Yadav, N Immorlica, E Rice, M Tambe International Conference on Autonomous Agents and Multiagent Systems 17 …, 2017 | 58 | 2017 |
| Learning to prescribe interventions for tuberculosis patients using digital adherence data JA Killian, B Wilder, A Sharma, V Choudhary, B Dilkina, M Tambe Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 53 | 2019 |
| Designing fair, efficient, and interpretable policies for prioritizing homeless youth for housing resources MJ Azizi, P Vayanos, B Wilder, E Rice, M Tambe Integration of Constraint Programming, Artificial Intelligence, and …, 2018 | 53 | 2018 |
| Exploring algorithmic fairness in robust graph covering problems A Rahmattalabi, P Vayanos, A Fulginiti, E Rice, B Wilder, A Yadav, ... Advances in Neural Information Processing Systems, 2020 | 43 | 2020 |
| End-to-End Influence Maximization in the Field. B Wilder, L Onasch-Vera, J Hudson, J Luna, N Wilson, R Petering, D Woo, ... International Conference on Autonomous Agents and Multiagent Systems 18 …, 2018 | 42 | 2018 |
| The role of age distribution and family structure on COVID-19 dynamics: A preliminary modeling assessment for Hubei and Lombardy B Wilder, M Charpignon, JA Killian, HC Ou, A Mate, S Jabbari, A Perrault, ... Available at SSRN 3564800, 2020 | 41 | 2020 |
| Inferring individual-level processes from population-level patterns in cultural evolution A Kandler, B Wilder, L Fortunato Royal Society Open Science 4 (9), 170949, 2017 | 39 | 2017 |
| Optimizing Network Structure for Preventative Health. B Wilder, HC Ou, K de la Haye, M Tambe International Conference on Autonomous Agents and Multiagent Systems, 841-849, 2018 | 37 | 2018 |
