| Normalizing kalman filters for multivariate time series analysis E de Bézenac, SS Rangapuram, K Benidis, M Bohlke-Schneider, R Kurle, ... Advances in Neural Information Processing Systems 33, 2995-3007, 2020 | 107 | 2020 |
| Forecasting with trees T Januschowski, Y Wang, K Torkkola, T Erkkilä, H Hasson, J Gasthaus International Journal of Forecasting 38 (4), 1473-1481, 2022 | 72 | 2022 |
| Accurate and interpretable machine learning for transparent pricing of health insurance plans R Kshirsagar, LY Hsu, CH Greenberg, M McClelland, A Mohan, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (17), 15127 …, 2021 | 11 | 2021 |
| Suzuki-invariant codes from the Suzuki curve A Eid, H Hasson, A Ksir, J Peachey Designs, Codes and Cryptography 81, 413-425, 2016 | 11 | 2016 |
| Probabilistic forecasting: A level-set approach H Hasson, B Wang, T Januschowski, J Gasthaus Advances in neural information processing systems 34, 6404-6416, 2021 | 10 | 2021 |
| But are you sure? an uncertainty-aware perspective on explainable ai C Marx, Y Park, H Hasson, Y Wang, S Ermon, L Huan International Conference on Artificial Intelligence and Statistics, 7375-7391, 2023 | 9 | 2023 |
| Prime-to-𝑝 étale fundamental groups of punctured projective lines over strictly Henselian fields H Hasson, J Yelton Transactions of the American Mathematical Society 373 (5), 3009-3030, 2020 | 6 | 2020 |
| Robust multivariate time-series forecasting: adversarial attacks and defense mechanisms L Liu, Y Park, TN Hoang, H Hasson, J Huan arXiv preprint arXiv:2207.09572, 2022 | 4 | 2022 |
| Towards robust multivariate time-series forecasting: adversarial attacks and defense mechanisms L Liu, Y Park, TN Hoang, H Hasson, J Huan KDD 2022 Workshop on Mining and Learning from Time Series-Deep Forecasting …, 2022 | 3 | 2022 |
| THE abc CONJECTURE IMPLIES THE WEAK DIVERSITY CONJECTURE H Hasson, A Obus Albanian Journal of Mathematics 12 (1), 8-14, 2018 | 3 | 2018 |
| Minimal fields of definition for Galois action H Hasson Journal of Pure and Applied Algebra 220 (9), 3327-3331, 2016 | 3 | 2016 |
| The prime-to-p part of étale fundamental groups of curves H Hasson University of Pennsylvania, 2012 | 3 | 2012 |
| Testing Causality for High Dimensional Data A Jambulapati, H Hasson, Y Park, Y Wang arXiv preprint arXiv:2303.07774, 2023 | 1 | 2023 |
| Dynamic Regret for Strongly Adaptive Methods and Optimality of Online KRR D Baby, H Hasson, Y Wang arXiv preprint arXiv:2111.11550, 2021 | 1 | 2021 |
| Arithmetic descent of specializations of Galois covers R Eberhart, H Hasson Functiones et Approximatio Commentarii Mathematici 56 (2), 259-270, 2017 | 1 | 2017 |
| On mere cover models of Galois covers, minimal fields of definition, and specializations H Hasson arXiv preprint arXiv:1310.4287, 2013 | 1 | 2013 |
| Theoretical guarantees of learning ensembling strategies with applications to time series forecasting H Hasson, DC Maddix, B Wang, G Gupta, Y Park International Conference on Machine Learning, 12616-12632, 2023 | | 2023 |
| Dynamic ensemble for probabilistic time-series forecasting via deep reinforcement learning Y Ding, Y Park, K Gopalswamy, H Hasson, B Wang, L Huan | | 2023 |
| But Are You Sure? Quantifying Uncertainty in Model Explanations CT Marx, Y Park, H Hasson, B Wang, S Ermon, L Huan Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022, 2022 | | 2022 |
| 8th SIGKDD International Workshop on Mining and Learning from Time Series--Deep Forecasting: Models, Interpretability, and Applications S Purushotham, J Huan, C Shen, D Song, Y Wang, J Gasthaus, H Hasson, ... Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | | 2022 |
