Valentin Flunkert

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 24

Top Topics

Exponential Smoothing

Demand Forecasting

Top Venues

Proc. VLDB Endow.

Publications

Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski
Deep Non-Parametric Time Series Forecaster. CoRR (2023)
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) (2023)
Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot
Criteria for Classifying Forecasting Methods. CoRR (2022)
Oliver Borchert, David Salinas, Valentin Flunkert, Tim Januschowski, Stephan Günnemann
Multi-Objective Model Selection for Time Series Forecasting. CoRR (2022)
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)
Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus
Neural Contextual Anomaly Detection for Time Series. IJCAI (2022)
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 (2022)
Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus
Neural Contextual Anomaly Detection for Time Series. CoRR (2021)
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 (2021)
Riccardo Grazzi, Valentin Flunkert, David Salinas, Tim Januschowski, Matthias W. Seeger, Cédric Archambeau
Meta-Forecasting by combining Global Deep Representations with Local Adaptation. CoRR (2021)
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 (2020)
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)
Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang
Forecasting Big Time Series: Theory and Practice. WWW (Companion Volume) (2020)
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 (2020)
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 (2020)
Valentin Flunkert, Quentin Rebjock, Joel Castellon, Laurent Callot, Tim Januschowski
A simple and effective predictive resource scaling heuristic for large-scale cloud applications. CoRR (2020)
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)
Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang
Forecasting Big Time Series: Theory and Practice. KDD (2019)
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 (2019)
Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski
Probabilistic Forecasting with Spline Quantile Function RNNs. AISTATS (2019)
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 (2017)
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) (2017)
Valentin Flunkert, David Salinas, Jan Gasthaus
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks. CoRR (2017)
Matthias W. Seeger, David Salinas, Valentin Flunkert
Bayesian Intermittent Demand Forecasting for Large Inventories. NIPS (2016)