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DiffFind: Discovering Differential Equations from Time Series.

, , , и . PAKDD (6), том 14650 из Lecture Notes in Computer Science, стр. 175-187. Springer, (2024)

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Sheng-chieh Lee

Cheng-Chieh Lee

Meng-Larn Lee

Meng Meng

Meng Meng Liang

 

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TgraphSpot: Fast and Effective Anomaly Detection for Time-Evolving Graphs., , , , , , , , и . IEEE Big Data, стр. 2214-2217. IEEE, (2022)Robust Sensor-based Human Activity Recognition with Snippet Consensus Neural Networks., , , , и . BSN, стр. 1-4. IEEE, (2019)VisPaD: Visualization and Pattern Discovery for Fighting Human Trafficking., , , , , , , , и . WWW (Companion Volume), стр. 273-277. ACM, (2022)TgrApp: Anomaly Detection and Visualization of Large-Scale Call Graphs., , , , , , , , , и . AAAI, стр. 16410-16412. AAAI Press, (2023)AutoAudit: Mining Accounting and Time-Evolving Graphs., , , , , , и . IEEE BigData, стр. 950-956. IEEE, (2020)DeepIdentifier: A Deep Learning-Based Lightweight Approach for User Identity Recognition., , , , и . ADMA, том 11888 из Lecture Notes in Computer Science, стр. 389-405. Springer, (2019)NETEFFECT: Discovery and Exploitation of Generalized Network Effects., , , и . PAKDD (1), том 14645 из Lecture Notes in Computer Science, стр. 299-312. Springer, (2024)DiffFind: Discovering Differential Equations from Time Series., , , и . PAKDD (6), том 14650 из Lecture Notes in Computer Science, стр. 175-187. Springer, (2024)End-To-End Self-tuning Self-supervised Time Series Anomaly Detection., , , , , и . CoRR, (2024)Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining., , , и . KDD, стр. 3128-3139. ACM, (2023)