| Predicting University Students' Academic Success and Major using Random Forests C Beaulac, JS Rosenthal Research in Higher Education 60, 1048–1064, 2019 | 36* | 2019 |
| BEST : A decision tree algorithm that handles missing values C Beaulac, JS Rosenthal Computational Statistics 35, 1001–1026, 2020 | 5 | 2020 |
| A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis C Beaulac, JS Rosenthal, D Hodgson Proceedings of the Machine Learning for Health (ML4H) Workshop at NeurIPS 2018, 2018 | 3 | 2018 |
| An evaluation of machine learning techniques to predict the outcome of children treated for Hodgkin-Lymphoma on the AHOD0031 trial C Beaulac, JS Rosenthal, Q Pei, D Friedman, S Wolden, D Hodgson Applied Artificial Intelligence 34 (14), 1100-1114, 2020 | 2 | 2020 |
| Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agent’s Location Using Hidden Markov Models C Beaulac, F Larribe International Journal of Computer Games Technology 2017, 2017 | 2 | 2017 |
| Intelligence artificielle avec apprentissage automatique pour l'estimation de la position d'un agent mobile en utilisant les modèles de Markov cachés C Beaulac Université du Québec à Montréal, 2015 | 2 | 2015 |
| Analysis of a high-resolution hand-written digits data set with writer characteristics C Beaulac, JS Rosenthal https://arxiv.org/abs/2011.07946, 2020 | 1 | 2020 |
| Performance and accessibility of statistical learning algorithms for applied data analysis C Beaulac University of Toronto, 2021 | | 2021 |
Jeffrey S. RosenthalProfessor of Statistics, University of TorontoVerified email at math.toronto.edu
