| 2025 | HAIS | Channel Selection and Creation Algorithms for Electroencephalography Classification with HIVE-COTE. | Aiden Rushbrooke, Matthew Middlehurst, Saber Sami, Anthony J. Bagnall |
| 2024 | KDD | 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 |
| 2023 | IC3K | Barycentre Averaging for the Move-Split-Merge Time Series Distance Measure. | Christopher Holder, David Guijo-Rubio, Anthony J. Bagnall |
| 2023 | IWANN | Time Series Classification of Electroencephalography Data. | Aiden Rushbrooke, Jordan Tsigarides, Saber Sami, Anthony J. Bagnall |
| 2020 | IJCNN | Time series ordinal classification via shapelets. | David Guijo-Rubio, Pedro Antonio Gutirrez, Anthony J. Bagnall, Csar Hervs-Martnez |
| 2020 | SGAI | Developing Ensemble Methods for Detecting Anomalies in Water Level Data. | Thakolpat Khampuengson, Anthony J. Bagnall, Wenjia Wang |
| 2019 | HAIS | Can Automated Smoothing Significantly Improve Benchmark Time Series Classification Algorithms? | James Large, Paul Southam, Anthony J. Bagnall |
| 2019 | IDEAL | Classifying Flies Based on Reconstructed Audio Signals. | Michael Flynn, Anthony J. Bagnall |
| 2019 | IDEAL | A Hybrid Approach to Time Series Classification with Shapelets. | David Guijo-Rubio, Pedro Antonio Gutirrez, Romain Tavenard, Anthony J. Bagnall |
| 2019 | IDEAL | Mixing Hetero- and Homogeneous Models in Weighted Ensembles. | James Large, Anthony J. Bagnall |
| 2019 | IDEAL | Scalable Dictionary Classifiers for Time Series Classification. | Matthew Middlehurst, William Vickers, Anthony J. Bagnall |
| 2018 | ICDM | Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios. | Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh |
| 2018 | PAKDD | Detecting Forged Alcohol Non-invasively Through Vibrational Spectroscopy and Machine Learning. | James Large, E. Kate Kemsley, Nikolaus Wellner, Ian Goodall, Anthony J. Bagnall |
| 2016 | ICDE | Time-series classification with COTE: The collective of transformation-based ensembles. | Anthony J. Bagnall, Jason Lines, Jon Hills, Aaron Bostrom |
| 2016 | ICDM | HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles for Time Series Classification. | Jason Lines, Sarah Taylor, Anthony J. Bagnall |
| 2015 | DaWaK | Binary Shapelet Transform for Multiclass Time Series Classification. | Aaron Bostrom, Anthony J. Bagnall |
| 2015 | IJCNN | Benchmarking the semi-supervised nave Bayes classifier. | Awat A. Saeed, Gavin C. Cawley, Anthony J. Bagnall |
| 2014 | SDM | Ensembles of Elastic Distance Measures for Time Series Classification. | Jason Lines, Anthony J. Bagnall |
| 2013 | ICPRAM | Clupea Harengus: Intraspecies Distinction using Curvature Scale Space and Shapelets - Classification of North-sea and Thames Herring using Boundary Contour of Sagittal Otoliths. | James Mapp, Mark Fisher, Anthony J. Bagnall, Jason Lines, Sally Warne, Joe Scutt Phillips |
| 2012 | IDEAL | Automated Bone Age Assessment Using Feature Extraction. | Luke M. Davis, Barry-John Theobald, Anthony J. Bagnall |
| 2012 | IDEAL | Interestingness Measures for Fixed Consequent Rules. | Jon Hills, Luke M. Davis, Anthony J. Bagnall |
| 2012 | IDEAL | Alternative Quality Measures for Time Series Shapelets. | Jason Lines, Anthony J. Bagnall |
| 2012 | KDD | A shapelet transform for time series classification. | Jason Lines, Luke M. Davis, Jon Hills, Anthony J. Bagnall |
| 2012 | SDM | Transformation Based Ensembles for Time Series Classification. | Anthony J. Bagnall, Luke M. Davis, Jon Hills, Jason Lines |
| 2011 | IDEAL | On the Extraction and Classification of Hand Outlines. | Luke M. Davis, Barry-John Theobald, Andoni Toms, Anthony J. Bagnall |
| 2011 | IDEAL | Classification of Household Devices by Electricity Usage Profiles. | Jason Lines, Anthony J. Bagnall, Patrick Caiger-Smith, Simon Anderson |
| 2010 | IDEAL | A Randomized Sphere Cover Classifier. | Reda Younsi, Anthony J. Bagnall |
| 2006 | IJCNN | Variance Stabilizing Regression Ensembles for Environmental Models. | Anthony J. Bagnall, Ian M. Whittley, Matthew Studley, Mike Pettipher, Firat Tekiner, Larry Bull |
| 2005 | CEC | On the use of rule-sharing in learning classifier system ensembles. | Larry Bull, Matthew Studley, Anthony J. Bagnall, Ian M. Whittley |
| 2005 | CEC | AgentP classifier system: self-adjusting vs. gradual approach. | Zhanna V. Zatuchna, Anthony J. Bagnall |
| 2005 | PAKDD | A Likelihood Ratio Distance Measure for the Similarity Between the Fourier Transform of Time Series. | Gareth J. Janacek, Anthony J. Bagnall, M. Powell |
| 2005 | PAKDD | A Novel Bit Level Time Series Representation with Implication of Similarity Search and Clustering. | Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh, Anthony J. Bagnall, Stefano Lonardi |
| 2004 | IDEAL | Improving Decision Tree Performance Through Induction- and Cluster-Based Stratified Sampling. | Abdul Aziz Gill, George D. Smith, Anthony J. Bagnall |
| 2004 | KDD | Clustering time series from ARMA models with clipped data. | Anthony J. Bagnall, Gareth J. Janacek |
| 2003 | CEC | Data mining rules using multi-objective evolutionary algorithms. | Beatriz de la Iglesia, M. S. Philpott, Anthony J. Bagnall, Victor J. Rayward-Smith |
| 2003 | IJCNN | Learning classifier systems for data mining: a comparison of XCS with other classifiers for the Forest Cover data set. | Anthony J. Bagnall, Gavin C. Cawley |
| 2000 | GECCO | A Multi-Adaptive Agent Model of Generator Bidding in the UK Market in Electricity. | Anthony J. Bagnall |
| 1999 | GECCO | Using an Adaptive Agent to Bid in a Simplified Model of the UK Market in Electricity. | Anthony J. Bagnall, George D. Smith |