| Adversarial time-to-event modeling P Chapfuwa, C Tao, C Li, C Page, B Goldstein, L Carin, R Henao International Conference on Machine Learning, 735-744, 2018 | 129 | 2018 |
| Nash: Toward end-to-end neural architecture for generative semantic hashing D Shen, Q Su, P Chapfuwa, W Wang, G Wang, L Carin, R Henao Association for Computational Linguistics, 2041-2050, 2018 | 65 | 2018 |
| Survival cluster analysis P Chapfuwa, C Li, N Mehta, L Carin, R Henao Proceedings of the ACM Conference on Health, Inference, and Learning, 60-68, 2020 | 48 | 2020 |
| Enabling counterfactual survival analysis with balanced representations P Chapfuwa, S Assaad, S Zeng, MJ Pencina, L Carin, R Henao Proceedings of the Conference on Health, Inference, and Learning, 133-145, 2021 | 31* | 2021 |
| Calibration and uncertainty in neural time-to-event modeling P Chapfuwa, C Tao, C Li, I Khan, KJ Chandross, MJ Pencina, L Carin, ... IEEE transactions on neural networks and learning systems 34 (4), 1666-1680, 2020 | 15* | 2020 |
| AIRIVA: a deep generative model of adaptive immune repertoires MF Pradier, N Prasad, P Chapfuwa, S Ghalebikesabi, M Ilse, ... Machine Learning for Healthcare Conference, 588-611, 2023 | 6 | 2023 |
| Antigen-driven expansion of public clonal T cell populations in inflammatory bowel diseases M Pesesky, R Bharanikumar, L Le Bourhis, H ElAbd, E Rosati, CL Carty, ... bioRxiv, 2024.05. 15.594220, 2024 | 1 | 2024 |
| Hawkes Process with Flexible Triggering Kernels Y Isik, P Chapfuwa, C Davis, R Henao Machine Learning for Healthcare Conference, 308-320, 2023 | 1* | 2023 |
| Probabilistic Time-to-Event Modeling Approaches for Risk Profiling P Chapfuwa Duke University, 2021 | 1 | 2021 |
| Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations P Chapfuwa, S Rose, L Carin, E Meeds, R Henao Conference on Uncertainty in Artificial Intelligence, 2022 | | 2022 |
Ricardo HenaoDuke UniversityVerified email at duke.edu
