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Benjamin Leblanc

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2020 – today

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2024
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  - conf/xai/LeblancG24
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Benjamin Leblanc, Pascal Germain:
Seeking Interpretability and Explainability in Binary Activated Neural Networks. xAI (1) 2024: 3-20
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  - journals/corr/abs-2410-13577
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Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours, Alexandre Drouin, Pascal Germain:
Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning. CoRR abs/2410.13577 (2024)
2023
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  - conf/ai/Fortier-DuboisL23
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Louis Fortier-Dubois, Benjamin Leblanc, Gaël Letarte, François Laviolette, Pascal Germain:
PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations. Canadian AI 2023
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  - journals/corr/abs-2311-11491
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Benjamin Leblanc, Pascal Germain:
Interpretability in Machine Learning: on the Interplay with Explainability, Predictive Performances and Models. CoRR abs/2311.11491 (2023)
2022
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  - journals/corr/abs-2209-03450
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Benjamin Leblanc, Pascal Germain:
A Greedy Algorithm for Building Compact Binary Activated Neural Networks. CoRR abs/2209.03450 (2022)
2021
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  - journals/corr/abs-2110-15137
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Louis Fortier-Dubois, Gaël Letarte, Benjamin Leblanc, François Laviolette, Pascal Germain:
Learning Aggregations of Binary Activated Neural Networks with Probabilities over Representations. CoRR abs/2110.15137 (2021)

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