Scalable Dictionary Classifiers for Time Series Classification. - Matthew Middlehurst; William Vickers; Anthony J. Bagnall (IDEAL (1), 2019)

A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency. - Anthony J. Bagnall; Franz J. Király; Markus Löning; Matthew Middlehurst; George Oastler (CoRR, 2019)

A tale of two toolkits, report the second: bake off redux. Chapter 1. dictionary based classifiers. - Anthony J. Bagnall; James Large; Matthew Middlehurst (CoRR, 2019)

The Canonical Interval Forest (CIF) Classifier for Time Series Classification. - Matthew Middlehurst; James Large; Anthony J. Bagnall (IEEE BigData, 2020)

On the Usage and Performance of the Hierarchical Vote Collective of Transformation-Based Ensembles Version 1.0 (HIVE-COTE v1.0). - Anthony J. Bagnall; Michael Flynn; James Large; Jason Lines; Matthew Middlehurst (AALTD@PKDD/ECML, 2020)

The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification. - Matthew Middlehurst; James Large; Gavin C. Cawley; Anthony J. Bagnall (ECML/PKDD (1), 2020)

A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0. - Anthony J. Bagnall; Michael Flynn; James Large; Jason Lines; Matthew Middlehurst (CoRR, 2020)

The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. - Alejandro Pasos Ruiz; Michael Flynn; James Large; Matthew Middlehurst; Anthony J. Bagnall (Data Min. Knowl. Discov., 2021)

HIVE-COTE 2.0: a new meta ensemble for time series classification. - Matthew Middlehurst; James Large; Michael Flynn; Jason Lines; Aaron Bostrom; Anthony J. Bagnall (Mach. Learn., 2021)

The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier. - Matthew Middlehurst; Anthony J. Bagnall (ICPRAI (2), 2022)

Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression. - Matthew Middlehurst; Anthony J. Bagnall (AALTD@ECML/PKDD, 2023)

A Hands-on Introduction to Time Series Classification and Regression. - Anthony J. Bagnall; Matthew Middlehurst; Germain Forestier; Ali Ismail-Fawaz; Antoine Guillaume; David Guijo-Rubio; Chang Wei Tan; Angus Dempster; Geoffrey I. Webb (KDD, 2024)

aeon: a Python toolkit for learning from time series. - Matthew Middlehurst; Ali Ismail-Fawaz; Antoine Guillaume; Christopher Holder; David Guijo-Rubio; Guzal Bulatova; Leonidas Tsaprounis; Lukasz Mentel; Martin Walter; Patrick Schäfer 001; Anthony J. Bagnall (CoRR, 2024)

A review and evaluation of elastic distance functions for time series clustering. - Christopher Holder; Matthew Middlehurst; Anthony J. Bagnall (Knowl. Inf. Syst., 2024)

Unsupervised feature based algorithms for time series extrinsic regression. - David Guijo-Rubio; Matthew Middlehurst; Guilherme Arcencio; Diego Furtado Silva; Anthony J. Bagnall (Data Min. Knowl. Discov., 2024)

Bake off redux: a review and experimental evaluation of recent time series classification algorithms. - Matthew Middlehurst; Patrick Schäfer 001; Anthony J. Bagnall (Data Min. Knowl. Discov., 2024)

Correction: Bake off redux: a review and experimental evaluation of recent time series classification algorithms. - Matthew Middlehurst; Patrick Schäfer 001; Anthony J. Bagnall (Data Min. Knowl. Discov., 2024)