mlsanityData to 7 Oct 2026

aeon: a Python toolkit for learning from time series

arXiv 2406.14231 ↗First posted 20 Jun 2024cs.LGcited by 46

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Abstract (arXiv)

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 regression and clustering, as well as a variety of utilities, transformations and distance measures designed for time series data. aeon also has a number of experimental modules for tasks such as anomaly detection, similarity search and segmentation. aeon follows the scikit-learn API as much as possible to help new users and enable easy integration of aeon estimators with useful tools such as model selection and pipelines. It provides a broad library of time series algorithms, including efficient implementations of the very latest advances in research. Using a system of optional dependencies, aeon integrates a wide variety of packages into a single interface while keeping the core framework with minimal dependencies. The package is distributed under the 3-Clause BSD license and is available at https://github.com/ aeon-toolkit/aeon. This version was submitted to the JMLR journal on 02 Nov 2023 for v0.5.0 of aeon. At the time of this preprint aeon has released v0.9.0, and has had substantial changes.

Key facts. Cited by 46 papers in the map (data through 7 Oct 2026). Builds on 26 of its 53 references that are in the map. First posted on arXiv 20 Jun 2024.

Builds on

26 of 53 references.

References · 26

  1. 2018Deep learning for time series classification: a reviewcited by 575
  2. 2019InceptionTime: Finding AlexNet for Time Series Classificationcited by 386
  3. 2019ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernelscited by 336
  4. 2021HIVE-COTE 2.0: a new meta ensemble for time series classificationcited by 118
  5. 2019catch22: CAnonical Time-series CHaracteristicscited by 103
  6. 2023Bake off redux: a review and experimental evaluation of recent time series classification algorithmscited by 99
  7. 2019sktime: A Unified Interface for Machine Learning with Time Seriescited by 98
  8. 2021MultiRocket: Multiple pooling operators and transformations for fast and effective time series classificationcited by 89
  9. 2013A Time Series Forest for Classification and Feature Extractioncited by 69
  10. 2023Deep Learning for Time Series Classification and Extrinsic Regression: A Current Surveycited by 68
  11. 2020The Canonical Interval Forest (CIF) Classifier for Time Series Classificationcited by 48
  12. 2018Proximity Forest: An effective and scalable distance-based classifier for time seriescited by 46
14 more
  1. 2023An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Setcited by 27
  2. 2021The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classificationcited by 26
  3. 2021Random Dilated Shapelet Transform: A New Approach for Time Series Shapeletscited by 22
  4. 2022ClaSP -- Parameter-free Time Series Segmentationcited by 21
  5. 2022The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifiercited by 18
  6. 2023WEASEL 2.0 -- A Random Dilated Dictionary Transform for Fast, Accurate and Memory Constrained Time Series Classificationcited by 15
  7. 2022A Review and Evaluation of Elastic Distance Functions for Time Series Clusteringcited by 14
  8. 2019Anomaly Detection in High Dimensional Datacited by 9
  9. 2023Unsupervised Feature Based Algorithms for Time Series Extrinsic Regressioncited by 9
  10. 2022Scalable Classifier-Agnostic Channel Selection for Multivariate Time Series Classificationcited by 8
  11. 2016Greedy Gaussian Segmentation of Multivariate Time Seriescited by 7
  12. 2021MrSQM: Fast Time Series Classification with Symbolic Representationscited by 7
  13. 2023ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter Averagingcited by 6
  14. 2023RED CoMETS: An ensemble classifier for symbolically represented multivariate time seriescited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 9; 2025: 14; 2026: 23.

46 papers.

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  1. 2024Look Into the LITE in Deep Learning for Time Series Classificationcited by 9
  2. 2025Pre-trained Forecasting Models: Strong Zero-Shot Feature Extractors for Time Series Classificationcited by 9
  3. 2024TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Modelscited by 8
  4. 2024Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classificationcited by 7
  5. 2025Random Feature Representation Boostingcited by 4
  6. 2026RocketPFN: Accurate Time Series Classification via In-Context Learningcited by 4
  7. 2024Early Classification of Time Series: A Survey and Benchmarkcited by 3
  8. 2025NILMFormer: Non-Intrusive Load Monitoring that Accounts for Non-Stationaritycited by 3
  9. 2026The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classificationcited by 3
  10. 2026MambaSL: Exploring Single-Layer Mamba for Time Series Classificationcited by 3
  11. 2024Time series classification with random convolution kernels: pooling operators and input representations mattercited by 2
  12. 2024On time series clustering with k-meanscited by 2
34 more
  1. 2024Using matrix-product states for time-series machine learningcited by 2
  2. 2025Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analyticscited by 2
  3. 2025TOC-UCO: a comprehensive repository of tabular ordinal classification datasetscited by 2
  4. 2025A Standardized Benchmark for Skeleton-Based Rehabilitation Assessment Using Deep Learningcited by 2
  5. 2024ml_edm package: a Python toolkit for Machine Learning based Early Decision Makingcited by 1
  6. 2024Rock the KASBA: Blazingly Fast and Accurate Time Series Clusteringcited by 1
  7. 2025Aggregating Local Saliency Maps for Semi-Global Explainable Image Classificationcited by 1
  8. 2025An Empirical Evaluation of Factors Affecting SHAP Explanation of Time Series Classificationcited by 1
  9. 2025Watch Your Step: A Cost-Sensitive Framework for Accelerometer-Based Fall Detection in Real-World Streaming Scenarioscited by 1
  10. 2025Label-Guided Imputation via Forest-Based Proximities for Improved Time Series Classificationcited by 1
  11. 2026A Sobering Look at Tabular Data Generation via Probabilistic Circuitscited by 1
  12. 2026Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verificationcited by 1
  13. 2026A Causal DAG Prior for Synthetic Time-Series Classification Datasetscited by 1
  14. 2026TS2TabPFN: Time Series Classification and Extrinsic Regression through Feature Extraction and a Tabular Foundation Modelcited by 1
  15. 2026Negation Beyond the Verbal Channel: Temporal Multimodal Correlates in Dialoguecited by 1
  16. 2025Learning Interpretable Differentiable Logic Networks for Time-Series Classificationcited by 0
  17. 2025Effectiveness of High-Dimensional Distance Metrics on Solar Flare Time Seriescited by 0
  18. 2025Guided by Stars: Interpretable Concept Learning Over Time Series via Temporal Logic Semanticscited by 0
  19. 2025The Generalized Proximity Forestcited by 0
  20. 2026Rapid Augmentations for Time Series (RATS): A High-Performance Library for Time Series Augmentationcited by 0
  21. 2026CUROCKET: Optimizing ROCKET for GPUcited by 0
  22. 2026End-to-End Learning for Partially-Observed Time Series with PyPOTScited by 0
  23. 2026Soft-MSM: Differentiable Context-Aware Elastic Alignment for Time Seriescited by 0
  24. 2026Empowering VLMs for Few-Shot Multimodal Time Series Classification via Tailored Agentic Reasoningcited by 0
  25. 2026Frequency Domain Reservoir Computingcited by 0
  26. 2026Unified Zero-Shot Time Series Forecasting: A Darts Foundationcited by 0
  27. 2026TimEE: End-to-end Time Series Classification via In-Context Learningcited by 0
  28. 2026Scaling Time Series Classification via XAI-Driven Data Reductioncited by 0
  29. 2026ADABORD: a novel AdaBoost approach for ordinal classificationcited by 0
  30. 2026IMFACT: Counterfactual Explanations for Time Series via Intrinsic Mode Function Substitutioncited by 0
  31. 2026Beyond Simulated Benchmarks: Evaluating Motion Representations for Fall Detection Under Real-World Data Scarcitycited by 0
  32. 2026Revisiting WEASEL 2.0: Reproduction, Sensitivity, and an Adaptive Ensemble-Size Rulecited by 0
  33. 2026Multi-Class Electrical and Mechanical Fault Classification Using Random Convolutional Kernelscited by 0
  34. 2026Continuous Online Fault Detection for Mobile Robots via Adaptive Edge Modelscited by 0