Francesco Alesiani
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    • Method for verifying information
    • LEO Satellite Orbit Prediction with Physics Informed Machine Learning
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    • Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
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    • Method and system for providing demand-responsive dispatching of a fleet of transportation vehicles, and a mobility-activity processing module for providing a mobility trace database
    • Method for incident detection in a time-evolving system
    • On learning from inaccurate and incomplete traffic flow data
    • Reinforcement learning-based bus holding for high-frequency services
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    • Locally growing rapid tree (LGRT) motion planning for autonomous driving
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    • A Scenario-Oriented Approach for Noise Detection on Traffic Flow Data
    • Drift3flow: Freeway-incident prediction using real-time learning
    • D2. 13-Final report eCoMessages
    • 2014 Index IEEE Intelligent Transportation Systems Magazine Vol. 6
    • A probabilistic activity model for predicting the mobility patterns of homogeneous social groups based on social network data
    • Educated rules for the prediction of human mobility patterns based on sparse social media and mobile phone data
    • Opportunistic solution-space reduction techniques for reducing the time complexity of dynamic speed control with microsimulation on motorways
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    • Afshin Abdi, Qualcomm Milad Abolpour, University of Oulu Ibrahim Abou-Faycal, American University of Beirut Maria Abu-Sini, Technion
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    • A Scenario-Oriented approach for Noise detection on Traffic Flow data
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LEO Satellite Orbit Prediction with Physics Informed Machine Learning

Sep 1, 2023·
Francesco Alesiani
,
Makoto Takamoto
,
Toshio Kamiya
,
Daisuke Etou
· 0 min read
Cite
Type
Journal article
Last updated on Sep 1, 2023
← Method for verifying information Oct 1, 2023
Method and system for scalable multi-task learning with convex clustering May 1, 2023 →

© 2024 Francesco Alesiani. This work is licensed under CC BY NC ND 4.0

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