| The Holdout Randomization Test for Feature Selection in Black Box Models W Tansey, V Veitch, H Zhang, R Rabadan, DM Blei Journal of Computational and Graphical Statistics, 2021 | 100* | 2021 |
| Annotation refactoring: inferring upgrade transformations for legacy applications W Tansey, E Tilevich Proceedings of the 23rd ACM SIGPLAN conference on Object-oriented …, 2008 | 74 | 2008 |
| False Discovery Rate Smoothing W Tansey, O Koyejo, RA Poldrack, JG Scott Journal of the American Statistical Association 113 (523), 1156-1171, 2018 | 69* | 2018 |
| Interpreting black box models via hypothesis testing C Burns, J Thomason, W Tansey Proceedings of the 2020 ACM-IMS on foundations of data science conference, 47-57, 2020 | 64* | 2020 |
| Quantile regression with ReLU networks: Estimators and minimax rates OHM Padilla, W Tansey, Y Chen Journal of Machine Learning Research 23 (247), 1-42, 2022 | 58 | 2022 |
| A fast and flexible algorithm for the graph-fused lasso W Tansey, JG Scott arXiv preprint arXiv:1505.06475, 2015 | 38 | 2015 |
| Multiagent learning through neuroevolution R Miikkulainen, E Feasley, L Johnson, I Karpov, P Rajagopalan, A Rawal, ... IEEE World Congress on Computational Intelligence, 24-46, 2012 | 31 | 2012 |
| Deep direct likelihood knockoffs M Sudarshan, W Tansey, R Ranganath Advances in neural information processing systems 33, 5036-5046, 2020 | 30 | 2020 |
| Multiscale spatial density smoothing: an application to large-scale radiological survey and anomaly detection W Tansey, A Athey, A Reinhart, JG Scott Journal of the American Statistical Association 112 (519), 1047-1063, 2017 | 30 | 2017 |
| Vector-space Markov Random Fields via Exponential Families W Tansey, OHM Padilla, AS Suggala, P Ravikumar Proceedings of The 32nd International Conference on Machine Learning 37, 684-692, 2015 | 30 | 2015 |
| Dose–response modeling in high-throughput cancer drug screenings: an end-to-end approach W Tansey, K Li, H Zhang, SW Linderman, R Rabadan, DM Blei, ... Biostatistics 23 (2), 643-665, 2022 | 26 | 2022 |
| Efficient automated marshaling of C++ data structures for MPI applications W Tansey, E Tilevich 2008 IEEE International Symposium on Parallel and Distributed Processing, 1-12, 2008 | 26 | 2008 |
| BayesTME: an end-to-end method for multiscale spatial transcriptional profiling of the tissue microenvironment H Zhang, MV Hunter, J Chou, JF Quinn, M Zhou, RM White, W Tansey Cell systems 14 (7), 605-619. e7, 2023 | 24 | 2023 |
| Black Box FDR W Tansey, Y Wang, D Blei, R Rabadan International Conference on Machine Learning, 4867-4876, 2018 | 24 | 2018 |
| Immunometabolic coevolution defines unique microenvironmental niches in ccRCC C Tang, AX Xie, EM Liu, F Kuo, M Kim, RG DiNatale, M Golkaram, ... Cell metabolism 35 (8), 1424-1440. e5, 2023 | 20 | 2023 |
| A Bayesian active learning platform for scalable combination drug screens C Tosh, M Tec, JB White, JF Quinn, G Ibanez Sanchez, P Calder, AL Kung, ... Nature Communications 16 (1), 156, 2025 | 15 | 2025 |
| Leaf-smoothed hierarchical softmax for ordinal prediction W Tansey, K Pichotta, J Scott Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 12* | 2018 |
| A Bayesian model of dose-response for cancer drug studies W Tansey, C Tosh, DM Blei The Annals of Applied Statistics 16 (2), 680-705, 2022 | 10 | 2022 |
| Diet2Vec: Multi-scale analysis of massive dietary data W Tansey, EW Lowe Jr, JG Scott arXiv preprint arXiv:1612.00388, 2016 | 10 | 2016 |
| Accelerating evolution via egalitarian social learning W Tansey, E Feasley, R Miikkulainen Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012 | 10 | 2012 |
James G. ScottProfessor and Chair, Statistics and Data Science, University of Texas at AustinVerified email at mccombs.utexas.edu
