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2020 – today
- 2023
[j1]Konstantinos Benidis
, Syama Sundar Rangapuram, Valentin Flunkert, Yuyang Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, François-Xavier Aubet, Laurent Callot, Tim Januschowski:
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. ACM Comput. Surv. 55(6): 121:1-121:36 (2023)- [i11]Sigrid Passano Hellan, Huibin Shen, François-Xavier Aubet, David Salinas, Aaron Klein:
Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation. CoRR abs/2306.16916 (2023) - 2022
- [c6]Youngsuk Park, Danielle C. Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang:
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting. AISTATS 2022: 8127-8150 - [c5]Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus:
Multivariate Quantile Function Forecaster. AISTATS 2022: 10603-10621 - [c4]Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus:
Neural Contextual Anomaly Detection for Time Series. IJCAI 2022: 2843-2851 - [i10]Christian Bock, François-Xavier Aubet, Jan Gasthaus, Andrey Kan, Ming Chen, Laurent Callot:
Online Time Series Anomaly Detection with State Space Gaussian Processes. CoRR abs/2201.06763 (2022) - [i9]Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus:
Multivariate Quantile Function Forecaster. CoRR abs/2202.11316 (2022) - [i8]Déborah Sulem, Michele Donini, Muhammad Bilal Zafar, Francois-Xavier Aubet, Jan Gasthaus, Tim Januschowski, Sanjiv Das, Krishnaram Kenthapadi, Cédric Archambeau:
Diverse Counterfactual Explanations for Anomaly Detection in Time Series. CoRR abs/2203.11103 (2022) - 2021
- [i7]Elena Ehrlich, Laurent Callot, François-Xavier Aubet:
Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series. CoRR abs/2106.10952 (2021) - [i6]Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus:
Neural Contextual Anomaly Detection for Time Series. CoRR abs/2107.07702 (2021) - [i5]Daniel Zügner, François-Xavier Aubet, Victor Garcia Satorras, Tim Januschowski, Stephan Günnemann, Jan Gasthaus:
A Study of Joint Graph Inference and Forecasting. CoRR abs/2109.04979 (2021) - [i4]Youngsuk Park, Danielle C. Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang:
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting. CoRR abs/2111.06581 (2021) - [i3]François-Xavier Aubet, Daniel Zügner, Jan Gasthaus:
Monte Carlo EM for Deep Time Series Anomaly Detection. CoRR abs/2112.14436 (2021)
2010 – 2019
- 2019
- [c3]Mohammad Irfan Khan, Francois-Xavier Aubet, Marc-Oliver Pahl, Jérôme Härri:
Deep Learning-aided Resource Orchestration for Vehicular Safety Communication. Wireless Days 2019: 1-8 - [i2]Mohammad Irfan Khan, François-Xavier Aubet, Marc-Oliver Pahl, Jérôme Härri:
Deep Learning-aided Application Scheduler for Vehicular Safety Communication. CoRR abs/1901.08872 (2019) - [i1]François-Xavier Aubet, Dominic Danks, Yuchen Zhu:
EQuANt (Enhanced Question Answer Network). CoRR abs/1907.00708 (2019) - 2018
- [c2]Marc-Oliver Pahl, Francois-Xavier Aubet:
All Eyes on You: Distributed Multi-Dimensional IoT Microservice Anomaly Detection. CNSM 2018: 72-80 - [c1]Marc-Oliver Pahl, Francois-Xavier Aubet, Stefan Liebald:
Graph-based IoT microservice security. NOMS 2018: 1-3
Coauthor Index
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