Learning Aggregations of Binary Activated Neural Networks with Probabilities over Representations. - Louis Fortier-Dubois; Gaël Letarte; Benjamin Leblanc; François Laviolette; Pascal Germain (CoRR, 2021)

A Greedy Algorithm for Building Compact Binary Activated Neural Networks. - Benjamin Leblanc; Pascal Germain (CoRR, 2022)

PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations. - Louis Fortier-Dubois; Benjamin Leblanc; Gaël Letarte; François Laviolette; Pascal Germain (Canadian AI, 2023)

Interpretability in Machine Learning: on the Interplay with Explainability, Predictive Performances and Models. - Benjamin Leblanc; Pascal Germain (CoRR, 2023)

Seeking Interpretability and Explainability in Binary Activated Neural Networks. - Benjamin Leblanc; Pascal Germain (xAI (1), 2024)

Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning. - Benjamin Leblanc; Mathieu Bazinet; Nathaniel D'Amours; Alexandre Drouin; Pascal Germain (CoRR, 2024)