Valentin Flunkert

According to our database, Valentin Flunkert authored at least 20 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey.

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

ACM Comput. Surv., 2023

Deep Non-Parametric Time Series Forecaster.

Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski

CoRR, 2023

2022

Criteria for Classifying Forecasting Methods.

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

CoRR, 2022

Intrinsic Anomaly Detection for Multi-Variate Time Series.

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

CoRR, 2022

Multi-Objective Model Selection for Time Series Forecasting.

Oliver Borchert, David Salinas, Valentin Flunkert, Tim Januschowski, Stephan Günnemann

CoRR, 2022

Neural Contextual Anomaly Detection for Time Series.

Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series.

Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Shubham Kapoor, Rajbir-Singh Nirwan, Valentin Flunkert, Jan Gasthaus, Tim Januschowski

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Meta-Forecasting by combining Global Deep Representations with Local Adaptation.

Riccardo Grazzi, Valentin Flunkert, David Salinas, Tim Januschowski, Matthias W. Seeger, Cédric Archambeau

CoRR, 2021

2020

GluonTS: Probabilistic and Neural Time Series Modeling in Python.

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

J. Mach. Learn. Res., 2020

The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models.

Stephan Rabanser, Tim Januschowski, Valentin Flunkert, David Salinas, Jan Gasthaus

CoRR, 2020

Neural forecasting: Introduction and literature overview.

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

CoRR, 2020

Forecasting Big Time Series: Theory and Practice.

Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

A Simple and Effective Predictive Resource Scaling Heuristic for Large-scale Cloud Applications.

Quentin Rebjock, Valentin Flunkert, Tim Januschowski, Laurent Callot, Joel Castellon

Proceedings of the AIDB@VLDB 2020, 2020

Elastic Machine Learning Algorithms in Amazon SageMaker.

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

Proceedings of the 2020 International Conference on Management of Data, 2020

2019

GluonTS: Probabilistic Time Series Models in Python.

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

CoRR, 2019

Probabilistic Forecasting with Spline Quantile Function RNNs.

Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2017

Probabilistic Demand Forecasting at Scale.

Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias W. Seeger, Bernie Wang

Proc. VLDB Endow., 2017

Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale.

Matthias W. Seeger, Syama Sundar Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert

CoRR, 2017

DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks.

Valentin Flunkert, David Salinas, Jan Gasthaus

CoRR, 2017

2016

Bayesian Intermittent Demand Forecasting for Large Inventories.

Matthias W. Seeger, David Salinas, Valentin Flunkert

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016