9 citations · 9 across the 4 of their papers we have counts for
6 papers · 1 filter
Local Reference Geometry Residual Augmentation for Imbalanced Time Series Classification
Chuanhang Qiu, Yanran Xu, Yue Wang +1
Imbalanced time series classification is often addressed by changing the training distribution, objective, logits, or final threshold. These interventions address important biases,…
Soft-MSM: Differentiable Context-Aware Elastic Alignment for Time Series
Christopher Holder, Anthony Bagnall
Elastic distances like dynamic time warping (DTW) are central to time series machine learning because they compare sequences under local temporal misalignment. Soft-DTW is an adapt…
The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classification
Matthew Middlehurst, Aiden Rushbrooke, Ali Ismail-Fawaz +6
Time series machine learning (TSML) is a growing research field that spans a wide range of tasks. The popularity of established tasks such as classification, clustering, and extrin…
Rock the KASBA: Blazingly Fast and Accurate Time Series Clustering
Christopher Holder, Anthony Bagnall
Time series data has become increasingly prevalent across numerous domains, driving a growing demand for time series machine learning techniques. Among these, time series clusterin…
On time series clustering with k-means
Christopher Holder, Anthony Bagnall, Jason Lines
There is a long history of research into time series clustering using distance-based partitional clustering. Many of the most popular algorithms adapt k-means (also known as Lloyd'…
aeon: a Python toolkit for learning from time series
Matthew Middlehurst, Ali Ismail-Fawaz, Antoine Guillaume +8
aeon is a unified Python 3 library for all machine learning tasks involving time series. The package contains modules for time series forecasting, classification, extrinsic regress…