| Hico: A benchmark for recognizing human-object interactions in images YW Chao, Z Wang, Y He, J Wang, J Deng Proceedings of the IEEE international conference on computer vision, 1017-1025, 2015 | 413 | 2015 |
| Shapley flow: A graph-based approach to interpreting model predictions J Wang, J Wiens, S Lundberg International Conference on Artificial Intelligence and Statistics, 721-729, 2021 | 158 | 2021 |
| Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks J Oh, J Wang, J Wiens Proceedings of the 3rd Machine Learning for Healthcare Conference, 2018 | 73 | 2018 |
| Learning credible models J Wang, J Oh, H Wang, J Wiens Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 51 | 2018 |
| The Advantage of Doubling: A Deep Reinforcement Learning Approach to Studying the Double Team in the NBA J Wang, I Fox, J Skaza, N Linck, S Singh, J Wiens Proceedings of the 12th Annual MIT Sloan Sports Analytics Conference, 2018 | 33 | 2018 |
| Relaxed parameter sharing: effectively modeling time-varying relationships in clinical time-series J Oh, J Wang, S Tang, MW Sjoding, J Wiens Machine Learning for Healthcare Conference, 27-52, 2019 | 20* | 2019 |
| AdaSGD: Bridging the gap between SGD and Adam J Wang, J Wiens arXiv preprint arXiv:2006.16541, 2020 | 14 | 2020 |
| Learning concept credible models for mitigating shortcuts J Wang, S Jabbour, M Makar, M Sjoding, J Wiens Advances in neural information processing systems 35, 33343-33356, 2022 | 11 | 2022 |
| Predictive Response Optimization: Using Reinforcement Learning to Fight Online Social Network Abuse G Wilson, G Goh, Y Jiang, A Gupta, J Wang, D Freeman, F Dinuzzo USENIX Security 2025, 2025 | | 2025 |
| Using Expert Interpretation and Reasoning to Guide Model Selection in Machine Learning J Wang | | 2022 |
| Supplementary Material: HICO: A Benchmark for Recognizing Human-Object Interactions in Images YW Chao, Z Wang, Y He, J Wang, J Deng | | |
Jenna WiensUniversity of MichiganVerified email at umich.edu
