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 | 73* | 2021 |
Annotation refactoring: inferring upgrade transformations for legacy applications W Tansey, E Tilevich Proceedings of the 23rd ACM SIGPLAN conference on Object-oriented …, 2008 | 69 | 2008 |
False Discovery Rate Smoothing W Tansey, O Koyejo, RA Poldrack, JG Scott Journal of the American Statistical Association 113 (523), 1156-1171, 2018 | 58* | 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 | 57* | 2020 |
A fast and flexible algorithm for the graph-fused lasso W Tansey, JG Scott arXiv preprint arXiv:1505.06475, 2015 | 36 | 2015 |
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 | 28 | 2017 |
Multiagent learning through neuroevolution R Miikkulainen, E Feasley, L Johnson, I Karpov, P Rajagopalan, A Rawal, ... Advances in Computational Intelligence: IEEE World Congress on Computational …, 2012 | 28 | 2012 |
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 | 27 | 2015 |
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 |
Black Box FDR W Tansey, Y Wang, D Blei, R Rabadan International Conference on Machine Learning, 4867-4876, 2018 | 22 | 2018 |
Deep direct likelihood knockoffs M Sudarshan, W Tansey, R Ranganath Advances in neural information processing systems 33, 5036-5046, 2020 | 21 | 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 | 19 | 2022 |
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 | 17* | 2022 |
Leaf-smoothed hierarchical softmax for ordinal prediction W Tansey, K Pichotta, J Scott Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 11* | 2018 |
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 | 9 | 2023 |
Accelerating evolution via egalitarian social learning W Tansey, E Feasley, R Miikkulainen Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012 | 9 | 2012 |
Improved models for password guessing W Tansey University of Texas, Tech. Rep, 2011 | 9 | 2011 |
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 | 7 | 2023 |
Quantile regression with deep relu networks: Estimators and minimax rates OHM Padilla, W Tansey, Y Chen arXiv preprint arXiv:2010.08236, 2020 | 7 | 2020 |
Diet2Vec: Multi-scale analysis of massive dietary data W Tansey, EW Lowe Jr, JG Scott arXiv preprint arXiv:1612.00388, 2016 | 7 | 2016 |