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2020 – today
- 2023
[j3]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)- [i13]Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski:
Deep Non-Parametric Time Series Forecaster. CoRR abs/2312.14657 (2023) - 2022
- [c8]Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Shubham Kapoor, Rajbir-Singh Nirwan, Valentin Flunkert, Jan Gasthaus, Tim Januschowski:
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series. ICLR 2022 - [c7]Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus:
Neural Contextual Anomaly Detection for Time Series. IJCAI 2022: 2843-2851 - [i12]Oliver Borchert, David Salinas, Valentin Flunkert, Tim Januschowski, Stephan Günnemann:
Multi-Objective Model Selection for Time Series Forecasting. CoRR abs/2202.08485 (2022) - [i11]Stephan Rabanser, Tim Januschowski, Kashif Rasul, Oliver Borchert, Richard Kurle, Jan Gasthaus, Michael Bohlke-Schneider, Nicolas Papernot, Valentin Flunkert:
Intrinsic Anomaly Detection for Multi-Variate Time Series. CoRR abs/2206.14342 (2022) - [i10]Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot:
Criteria for Classifying Forecasting Methods. CoRR abs/2212.03523 (2022) - 2021
- [i9]Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus:
Neural Contextual Anomaly Detection for Time Series. CoRR abs/2107.07702 (2021) - [i8]Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Rajbir-Singh Nirwan, Shubham Kapoor, Valentin Flunkert, Jan Gasthaus, Tim Januschowski:
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series. CoRR abs/2108.00981 (2021) - [i7]Riccardo Grazzi, Valentin Flunkert, David Salinas, Tim Januschowski, Matthias W. Seeger, Cédric Archambeau:
Meta-Forecasting by combining Global Deep Representations with Local Adaptation. CoRR abs/2111.03418 (2021) - 2020
- [j2]Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Sundar Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang:
GluonTS: Probabilistic and Neural Time Series Modeling in Python. J. Mach. Learn. Res. 21: 116:1-116:6 (2020) - [c6]Edo Liberty, Zohar S. Karnin, Bing Xiang, Laurence Rouesnel, Baris Coskun, Ramesh Nallapati, Julio Delgado, Amir Sadoughi, Yury Astashonok, Piali Das, Can Balioglu, Saswata Chakravarty, Madhav Jha, Philip Gautier, David Arpin, Tim Januschowski, Valentin Flunkert, Yuyang Wang, Jan Gasthaus, Lorenzo Stella, Syama Sundar Rangapuram, David Salinas, Sebastian Schelter, Alex Smola:
Elastic Machine Learning Algorithms in Amazon SageMaker. SIGMOD Conference 2020: 731-737 - [c5]Quentin Rebjock, Valentin Flunkert, Tim Januschowski, Laurent Callot, Joel Castellon:
A Simple and Effective Predictive Resource Scaling Heuristic for Large-scale Cloud Applications. AIDB@VLDB 2020 - [c4]Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang:
Forecasting Big Time Series: Theory and Practice. WWW (Companion Volume) 2020: 320-321 - [i6]Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Bernie Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, Laurent Callot, Tim Januschowski:
Neural forecasting: Introduction and literature overview. CoRR abs/2004.10240 (2020) - [i5]Stephan Rabanser, Tim Januschowski, Valentin Flunkert, David Salinas, Jan Gasthaus:
The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models. CoRR abs/2005.10111 (2020) - [i4]Valentin Flunkert, Quentin Rebjock, Joel Castellon, Laurent Callot, Tim Januschowski:
A simple and effective predictive resource scaling heuristic for large-scale cloud applications. CoRR abs/2008.01215 (2020)
2010 – 2019
- 2019
- [c3]Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski:
Probabilistic Forecasting with Spline Quantile Function RNNs. AISTATS 2019: 1901-1910 - [c2]Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang:
Forecasting Big Time Series: Theory and Practice. KDD 2019: 3209-3210 - [i3]Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Sundar Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang:
GluonTS: Probabilistic Time Series Models in Python. CoRR abs/1906.05264 (2019) - 2017
- [j1]Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias W. Seeger, Bernie Wang:
Probabilistic Demand Forecasting at Scale. Proc. VLDB Endow. 10(12): 1694-1705 (2017) - [i2]Valentin Flunkert, David Salinas, Jan Gasthaus:
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks. CoRR abs/1704.04110 (2017) - [i1]Matthias W. Seeger, Syama Sundar Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert:
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale. CoRR abs/1709.07638 (2017) - 2016
- [c1]Matthias W. Seeger, David Salinas, Valentin Flunkert:
Bayesian Intermittent Demand Forecasting for Large Inventories. NIPS 2016: 4646-4654
Coauthor Index
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