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AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting., , , , , , and . CoRR, (2023)FastPoint: Scalable Deep Point Processes., , and . ECML/PKDD (2), volume 11907 of Lecture Notes in Computer Science, page 465-480. Springer, (2019)Testing for Self-excitation in Financial Events: A Bayesian Approach., and . MIDAS/PAP@PKDD/ECML, volume 11054 of Lecture Notes in Computer Science, page 95-102. Springer, (2018)Clustering Event Streams With Low Rank Hawkes Processes., , and . IEEE Signal Process. Lett., (2020)Dirichlet-Luce choice model for learning from interactions., , , and . User Model. User Adapt. Interact., 32 (4): 611-648 (2022)Deep Learning for Time Series Forecasting: Tutorial and Literature Survey., , , , , , , , , and 3 other author(s). ACM Comput. Surv., 55 (6): 121:1-121:36 (2023)GluonTS: Probabilistic Time Series Models in Python., , , , , , , , , and 3 other author(s). CoRR, (2019)A Review of Nonnegative Matrix Factorization Methods for Clustering.. CoRR, (2015)An application of deep learning for trade signal prediction in financial markets., and . SIU, page 2521-2524. IEEE, (2015)AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting., , , , , , and . AutoML, volume 224 of Proceedings of Machine Learning Research, page 9/1-21. PMLR, (2023)