Publications

Jaël Champagne Gareau, Daniel Lemire (2025). Converting Binary Floating-Point Numbers to Shortest Decimal Strings: An Experimental Review. Software: Practice and Experience.

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Mathieu Gravel, Jaël Champagne Gareau (2025). Topology-Driven Solver Selection for Stochastic Shortest Path MDPs via Explainable Machine Learning. Canadian AI 2025.

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Jaël Champagne Gareau (2024). Résolution efficace de processus décisionnels de Markov par l'exploitation d'approches structurelles et algorithmiques tirant parti de l'architecture moderne des ordinateurs. Université du Québec à Montréal.

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Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov (2024). Towards Topologically Diverse Probabilistic Planning Benchmarks. IFCS 2024.

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Jaël Champagne Gareau, Guillaume Gosset, Marc-André Lavoie, Éric Beaudry, Vladimir Makarenkov (2024). Increased Plan Stability in Cooperative Electric Vehicles Path-Planning. ICAPS'24 HAXP Workshop.

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Jaël Champagne Gareau, Marc-André Lavoie, Guillaume Gosset, Éric Beaudry (2024). Cooperative Electric Vehicles Planning. AAMAS 2024.

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Jaël Champagne Gareau, Guillaume Gosset, Éric Beaudry, Vladimir Makarenkov (2023). Cache-Efficient Dynamic Programming MDP Solver. ECAI 2023.

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Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov (2023). Fast and optimal branch-and-bound planner for the grid-based coverage path planning problem based on an admissible heuristic function. Frontiers in Robotics and AI.

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Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov (2022). pcTVI: Parallel MDP Solver Using a Decomposition Into Independent Chains. IFCS 2022.

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Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov (2022). Cache-Efficient Memory Representation of Markov Decision Processes. Canadian AI 2022.

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Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov (2021). Fast and Optimal Planner for the Discrete Grid-Based Coverage Path-Planning Problem. IDEAL 2021.

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Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov (2021). A Fast Electric Vehicle Path-Planner Using Clustering. IFCS 2019.

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Jonathan Milot, Jaël Champagne Gareau, Éric Beaudry (2020). An Energy-Efficient Method with Dynamic GPS Sampling Rate for Transport Mode Detection and Trip Reconstruction. Canadian AI 2020.

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Jaël Champagne Gareau (2019). Planification d'itinéraires pour véhicule électrique avec disponibilité incertaine des bornes de recharge. Université du Québec à Montréal.

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Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov (2019). An Efficient Electric Vehicle Path-Planner That Considers the Waiting Time. ACM SIGSPATIAL 2019.

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