19 citations · 22 across the 6 of their papers we have counts for
8 papers · 1 filter
MONSTER: Monash Scalable Time Series Evaluation Repository
Angus Dempster, Navid Mohammadi Foumani, Chang Wei Tan +6
We introduce MONSTER-the MONash Scalable Time Series Evaluation Repository-a collection of large datasets for time series classification. The field of time series classification ha…
Series2Vec: Similarity-based Self-supervised Representation Learning for Time Series Classification
Navid Mohammadi Foumani, Chang Wei Tan, Geoffrey I. Webb +2
We argue that time series analysis is fundamentally different in nature to either vision or natural language processing with respect to the forms of meaningful self-supervised lear…
FRANS: Automatic Feature Extraction for Time Series Forecasting
Alexey Chernikov, Chang Wei Tan, Pablo Montero-Manso +1
Feature extraction methods help in dimensionality reduction and capture relevant information. In time series forecasting (TSF), features can be used as auxiliary information to ach…
Classification of multivariate weakly-labelled time-series with attention
Surayez Rahman, Chang Wei Tan
This research identifies a gap in weakly-labelled multivariate time-series classification (TSC), where state-of-the-art TSC models do not per-form well. Weakly labelled time-series…
Time Series Extrinsic Regression
Chang Wei Tan, Christoph Bergmeir, Francois Petitjean +1
This paper studies Time Series Extrinsic Regression (TSER): a regression task of which the aim is to learn the relationship between a time series and a continuous scalar variable;…
Monash University, UEA, UCR Time Series Extrinsic Regression Archive
Chang Wei Tan, Christoph Bergmeir, Francois Petitjean +1
Time series research has gathered lots of interests in the last decade, especially for Time Series Classification (TSC) and Time Series Forecasting (TSF). Research in TSC has great…