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Criteria for Classifying Forecasting Methods


Dec 07, 2022
Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot

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On the detrimental effect of invariances in the likelihood for variational inference


Sep 15, 2022
Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus

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Intrinsic Anomaly Detection for Multi-Variate Time Series


Jun 29, 2022
Stephan Rabanser, Tim Januschowski, Kashif Rasul, Oliver Borchert, Richard Kurle, Jan Gasthaus, Michael Bohlke-Schneider, Nicolas Papernot, Valentin Flunkert

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Diverse Counterfactual Explanations for Anomaly Detection in Time Series


Mar 21, 2022
Deborah Sulem, Michele Donini, Muhammad Bilal Zafar, Francois-Xavier Aubet, Jan Gasthaus, Tim Januschowski, Sanjiv Das, Krishnaram Kenthapadi, Cedric Archambeau

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* 24 pages, 11 figures 

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Multivariate Quantile Function Forecaster


Feb 23, 2022
Kelvin Kan, Fran├žois-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus

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Online Time Series Anomaly Detection with State Space Gaussian Processes


Jan 18, 2022
Christian Bock, Fran├žois-Xavier Aubet, Jan Gasthaus, Andrey Kan, Ming Chen, Laurent Callot

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Monte Carlo EM for Deep Time Series Anomaly Detection


Dec 29, 2021
Fran├žois-Xavier Aubet, Daniel Z├╝gner, Jan Gasthaus

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* Presented at the ICML 2021 Time Series Workshop 

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Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting


Nov 12, 2021
Youngsuk Park, Danielle Maddix, Fran├žois-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang

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* 24 pages 

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A Study of Joint Graph Inference and Forecasting


Sep 10, 2021
Daniel Z├╝gner, Fran├žois-Xavier Aubet, Victor Garcia Satorras, Tim Januschowski, Stephan G├╝nnemann, Jan Gasthaus

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* Published at the ICML 2021 Time Series Workshop 

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Neural Contextual Anomaly Detection for Time Series


Jul 16, 2021
Chris U. Carmona, Fran├žois-Xavier Aubet, Valentin Flunkert, Jan Gasthaus

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* Chris and Fran\c{c}ois-Xavier contributed equally 

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