Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agent's Location Using Hidden Markov Models. - Cédric Beaulac; Fabrice Larribe (Int. J. Comput. Games Technol., 2017)

Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agents Location Using Hidden Markov Models. - Cédric Beaulac; Fabrice Larribe (CoRR, 2018)

Predicting University Students' Academic Success and Choice of Major using Random Forests. - Cédric Beaulac; Jeffrey S. Rosenthal (CoRR, 2018)

Handling Missing Values using Decision Trees with Branch-Exclusive Splits. - Cédric Beaulac; Jeffrey S. Rosenthal (CoRR, 2018)

A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis. - Cédric Beaulac; Jeffrey S. Rosenthal; David Hodgson (CoRR, 2018)

An evaluation of machine learning techniques to predict the outcome of children treated for Hodgkin-Lymphoma on the AHOD0031 trial. - Cédric Beaulac; Jeffrey S. Rosenthal; Qinglin Pei; Debra Friedman; Suzanne L. Wolden; David Hodgson (Appl. Artif. Intell., 2020)

Analysis of a high-resolution hand-written digits data set with writer characteristics. - Cédric Beaulac; Jeffrey S. Rosenthal (CoRR, 2020)

BEST: a decision tree algorithm that handles missing values. - Cédric Beaulac; Jeffrey S. Rosenthal (Comput. Stat., 2020)

Predicting Time-to-conversion for Dementia of Alzheimer's Type using Multi-modal Deep Survival Analysis. - Ghazal Mirabnahrazam; Da Ma; Cédric Beaulac; Sieun Lee; Karteek Popuri; Hyunwoo Lee 007; Jiguo Cao; James E. Galvin; Lei Wang; Mirza Faisal Beg; Alzheimer's Disease Neuroimaging Initiative (CoRR, 2022)

Introducing a New High-Resolution Handwritten Digits Data Set with Writer Characteristics. - Cédric Beaulac; Jeffrey S. Rosenthal (SN Comput. Sci., 2023)

A moment-matching metric for latent variable generative models. - Cédric Beaulac (Mach. Learn., 2023)

Neural networks for scalar input and functional output. - Sidi Wu; Cédric Beaulac; Jiguo Cao (Stat. Comput., 2023)

Neuroimaging feature extraction using a neural network classifier for imaging genetics. - Cédric Beaulac; Sidi Wu; Erin Gibson; Michelle F. Miranda; Jiguo Cao; Leno Rocha; Mirza Faisal Beg; Farouk S. Nathoo (BMC Bioinform., 2023)

Constructing Ancestral Recombination Graphs through Reinforcement Learning. - Mélanie Raymond; Marie-Hélène Descary; Cédric Beaulac; Fabrice Larribe (CoRR, 2024)

Functional autoencoder for smoothing and representation learning. - Sidi Wu; Cédric Beaulac; Jiguo Cao (Stat. Comput., 2024)