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Learning interaction rules from multi-animal trajectories via augmented behavioral models.

, , , , , , , , , , , , и . NeurIPS, стр. 11108-11122. (2021)

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Ken Lau

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Study on hypercompact and lightweight data logger separators for wild animals., , , , , , и . Adv. Robotics, 35 (2): 81-92 (2021)Travel Time-Dependent Maximum Entropy Inverse Reinforcement Learning for Seabird Trajectory Prediction., , , , и . ACPR, стр. 430-435. IEEE Computer Society, (2017)Preliminary analysis of the foraging strategy of seabirds on the basis of their behavior and physiological cost., , и . PerCom Workshops, стр. 697-699. IEEE, (2019)Investigation of Large-Scale Navigation Behavior of Echolocating Bats During Natural Foraging, Using GPS and Acoustic-GPS Data-Loggers., , , , и . PerCom Workshops, стр. 700-702. IEEE, (2019)Understanding Animal Behavior Using Their Trajectories - A Case Study of Gender Specific Trajectory Trends., , и . HCI (22), том 10922 из Lecture Notes in Computer Science, стр. 3-22. Springer, (2018)Trajectories Prediction of the Black-Tailed Gull Using the Inverse Reinforcement Learning., , , , , и . PerCom Workshops, стр. 715-717. IEEE, (2019)Fréchet Kernel for Trajectory Data Analysis., , , , , , , и . SIGSPATIAL/GIS, стр. 221-224. ACM, (2021)Does Aging Change Foraging Behavior of Black-Tailed Gulls?, , , и . PerCom Workshops, стр. 703-705. IEEE, (2019)Efficient learning algorithm for sparse subsequence pattern-based classification and applications to comparative animal trajectory data analysis., , , , , , , , , и 5 other автор(ы). Adv. Robotics, 33 (3-4): 134-152 (2019)Learning interaction rules from multi-animal trajectories via augmented behavioral models., , , , , , , , , и 3 other автор(ы). NeurIPS, стр. 11108-11122. (2021)