| The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process H Mei, J Eisner arXiv, 2016 | 336 | 2016 |
| What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment H Mei, M Bansal, MR Walter NAACL, 2016 | 251 | 2016 |
| Listen, attend, and walk: Neural mapping of navigational instructions to action sequences H Mei, M Bansal, MR Walter AAAI, 2016 | 197 | 2016 |
| Coherent Dialogue with Attention-based Language Models H Mei, M Bansal, MR Walter AAAI, 2017 | 94 | 2017 |
| Imputing missing events in continuous-time event streams H Mei, G Qin, J Eisner International Conference on Machine Learning, 4475-4485, 2019 | 16 | 2019 |
| Neural Datalog through time: Informed temporal modeling via logical specification H Mei, G Qin, M Xu, J Eisner International Conference on Machine Learning, 6808-6819, 2020 | 8 | 2020 |
| Accurate Vision-based Vehicle Localization using Satellite Imagery H Chu, H Mei, M Bansal, MR Walter NIPS 2015 Transfer and Multi-Task Learning workshop, 2015 | 7 | 2015 |
| Noise-contrastive estimation for multivariate point processes H Mei, T Wan, J Eisner arXiv preprint arXiv:2011.00717, 2020 | 5 | 2020 |
| Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction H Mei, S Zhang, K Duh, B Van Durme arXiv preprint arXiv:1805.08271, 2018 | 3 | 2018 |
| On the idiosyncrasies of the Mandarin Chinese classifier system S Liu, H Mei, A Williams, R Cotterell arXiv preprint arXiv:1902.10193, 2019 | 2 | 2019 |
| Personalized Dynamic Treatment Regimes in Continuous Time: A Bayesian Joint Model for Optimizing Clinical Decisions with Timing W Hua, H Mei, S Zohar, M Giral, Y Xu arXiv e-prints, arXiv: 2007.04155, 2020 | 1 | 2020 |
| Transformer Embeddings of Irregularly Spaced Events and Their Participants C Yang, H Mei, J Eisner arXiv preprint arXiv:2201.00044, 2021 | | 2021 |
| Neural Probabilistic Methods for Event Sequence Modeling H Mei Johns Hopkins University, 2021 | | 2021 |
| Personalized Dynamic Treatment Regimes in Continuous Time: A Bayesian Approach for Optimizing Clinical Decisions with Timing W Hua, H Mei, S Zohar, M Giral, Y Xu Bayesian Analysis 1 (1), 1-30, 2021 | | 2021 |
| Informed Temporal Modeling via Logical Specification of Factorial LSTMs H Mei, G Qin, M Xu, J Eisner | | 2019 |
| Inference of unobserved event streams with neural Hawkes particle smoothing H Mei, G Qin, J Eisner | | 2018 |
| Accurate Vision-based Localization by Transferring Between Ground and Satellite Images H Chu, H Mei, M Bansal, MR Walter | | |
Jason EisnerProfessor of Computer Science, Johns Hopkins UniversityVerified email at cs.jhu.edu
