77 citations · 107 across the 7 of their papers we have counts for
4 papers · 1 filter
Multi-Objective Model Selection for Time Series Forecasting
Oliver Borchert, David Salinas, Valentin Flunkert +2
Research on time series forecasting has predominantly focused on developing methods that improve accuracy. However, other criteria such as training time or latency are critical in…
Neural Contextual Anomaly Detection for Time Series
Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert +1
We introduce Neural Contextual Anomaly Detection (NCAD), a framework for anomaly detection on time series that scales seamlessly from the unsupervised to supervised setting, and is…
The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models
Stephan Rabanser, Tim Januschowski, Valentin Flunkert +2
Time series modeling techniques based on deep learning have seen many advancements in recent years, especially in data-abundant settings and with the central aim of learning global…
GluonTS: Probabilistic Time Series Models in Python
Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider +10
We introduce Gluon Time Series (GluonTS, available at https://gluon-ts.mxnet.io), a library for deep-learning-based time series modeling. GluonTS simplifies the development of and…