mlsanityData to 7 Oct 2026

Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey

arXiv 2302.02515 ↗First posted 6 Feb 2023cs.LG cs.AI cs.CVcited by 68

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Abstract (arXiv)

Time Series Classification and Extrinsic Regression are important and challenging machine learning tasks. Deep learning has revolutionized natural language processing and computer vision and holds great promise in other fields such as time series analysis where the relevant features must often be abstracted from the raw data but are not known a priori. This paper surveys the current state of the art in the fast-moving field of deep learning for time series classification and extrinsic regression. We review different network architectures and training methods used for these tasks and discuss the challenges and opportunities when applying deep learning to time series data. We also summarize two critical applications of time series classification and extrinsic regression, human activity recognition and satellite earth observation.

Key facts. Cited by 68 papers in the map (data through 7 Oct 2026). Builds on 117 of its 324 references that are in the map. First posted on arXiv 6 Feb 2023.

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117 of 324 references.

References · 117

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  4. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  5. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  6. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  7. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
  8. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,773
  9. 2017Squeeze-and-Excitation Networkscited by 4,763
  10. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
  11. 2014Going Deeper with Convolutionscited by 4,231
  12. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,016
38 more
  1. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  2. 2014Sequence to Sequence Learning with Neural Networkscited by 2,974
  3. 2019A Comprehensive Survey on Graph Neural Networkscited by 2,906
  4. 2018CBAM: Convolutional Block Attention Modulecited by 2,463
  5. 2015Learning Deep Features for Discriminative Localizationcited by 2,430
  6. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
  7. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,141
  8. 2016Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learningcited by 1,509
  9. 2017Deformable Convolutional Networkscited by 1,481
  10. 2015Spatial Transformer Networkscited by 1,423
  11. 2015Effective Approaches to Attention-based Neural Machine Translationcited by 1,024
  12. 2014Deep Visual-Semantic Alignments for Generating Image Descriptionscited by 966
  13. 2014Deep Learning in Neural Networks: An Overviewcited by 765
  14. 2020Self-supervised Learning: Generative or Contrastivecited by 693
  15. 2019Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecastingcited by 606
  16. 2018Deep learning for time series classification: a reviewcited by 575
  17. 2022Transformers in Time Series: A Surveycited by 489
  18. 2014Long-term Recurrent Convolutional Networks for Visual Recognition and Descriptioncited by 483
  19. 2021TS2Vec: Towards Universal Representation of Time Seriescited by 463
  20. 2020A Transformer-based Framework for Multivariate Time Series Representation Learningcited by 449
  21. 2018The UCR Time Series Archivecited by 421
  22. 2019InceptionTime: Finding AlexNet for Time Series Classificationcited by 386
  23. 2015Recent Advances in Convolutional Neural Networkscited by 360
  24. 2016Time Series Classification from Scratch with Deep Neural Networks: A Strong Baselinecited by 358
  25. 2021Time-Series Representation Learning via Temporal and Contextual Contrastingcited by 342
  26. 2019ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernelscited by 336
  27. 2018The UEA multivariate time series classification archive, 2018cited by 330
  28. 2018Scalable and accurate deep learning for electronic health recordscited by 275
  29. 2016Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICAcited by 270
  30. 2018CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenescited by 267
  31. 2019Unsupervised Scalable Representation Learning for Multivariate Time Seriescited by 267
  32. 2022Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistencycited by 246
  33. 2018Human Action Recognition and Prediction: A Surveycited by 226
  34. 2021Unsupervised Representation Learning for Time Series with Temporal Neighborhood Codingcited by 223
  35. 2021BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG datacited by 194
  36. 2020MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classificationcited by 186
  37. 2020Benchmarking Multivariate Time Series Classification Algorithmscited by 145
  38. 2017LSTM Fully Convolutional Networks for Time Series Classificationcited by 135

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 6; 2024: 14; 2025: 23; 2026: 25.

68 papers.

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  1. 2023A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detectioncited by 145
  2. 2023Bake off redux: a review and experimental evaluation of recent time series classification algorithmscited by 99
  3. 2025Time-MQA: Time Series Multi-Task Question Answering with Context Enhancementcited by 74
  4. 2024EEG2Rep: Enhancing Self-supervised EEG Representation Through Informative Masked Inputscited by 48
  5. 2024aeon: a Python toolkit for learning from time seriescited by 46
  6. 2023Improving Position Encoding of Transformers for Multivariate Time Series Classificationcited by 44
  7. 2024Universal Time-Series Representation Learning: A Surveycited by 28
  8. 2024ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysiscited by 26
  9. 2023Inherently Interpretable Time Series Classification via Multiple Instance Learningcited by 23
  10. 2024Deep Learning for Satellite Image Time Series Analysis: A Reviewcited by 13
  11. 2025Learning Soft Sparse Shapes for Efficient Time-Series Classificationcited by 10
  12. 2025Generalizable deep learning for photoplethysmography-based blood pressure estimation -- A Benchmarking Studycited by 9
38 more
  1. 2023Series2Vec: Similarity-based Self-supervised Representation Learning for Time Series Classificationcited by 8
  2. 2025Dynamic Black-box Backdoor Attacks on IoT Sensory Datacited by 8
  3. 2026TSAQA: Time Series Analysis Question And Answering Benchmarkcited by 8
  4. 2024QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models -- Extended Versioncited by 7
  5. 2024Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classificationcited by 7
  6. 2025MONSTER: Monash Scalable Time Series Evaluation Repositorycited by 6
  7. 2024FreqRISE: Explaining time series using frequency maskingcited by 4
  8. 2025ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Modelscited by 3
  9. 2026A Unified Shape-Aware Foundation Model for Time Series Classificationcited by 3
  10. 2026The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classificationcited by 3
  11. 2024Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classificationcited by 2
  12. 2024AI-driven Java Performance Testing: Balancing Result Quality with Testing Timecited by 2
  13. 2025An Analysis of Temporal Dropout in Earth Observation Time Series for Regression Taskscited by 2
  14. 2025Representation Learning of Limit Order Book: A Comprehensive Study and Benchmarkingcited by 2
  15. 2023Convolutional and Deep Learning based techniques for Time Series Ordinal Classificationcited by 1
  16. 2024Stochastic Sparse Sampling: A Framework for Variable-Length Medical Time Series Classificationcited by 1
  17. 2024TS-ACL: Closed-Form Solution for Time Series-oriented Continual Learningcited by 1
  18. 2024Longitudinal Ensemble Integration for sequential classification with multimodal datacited by 1
  19. 2025A 1-D CNN inference engine for constrained platformscited by 1
  20. 2025Concealed Adversarial attacks on neural networks for sequential datacited by 1
  21. 2025PTMs-TSCIL Pre-Trained Models Based Class-Incremental Learningcited by 1
  22. 2025STaRFormer: Semi-Supervised Task-Informed Representation Learning via Dynamic Attention-Based Regional Masking for Sequential Datacited by 1
  23. 2025Towards Migrating Neural Network Implementationscited by 1
  24. 2025SigTime: Learning and Visually Explaining Time Series Signaturescited by 1
  25. 2026Evo-TFS: Evolutionary Time-Frequency Domain-Based Synthetic Minority Oversampling Approach to Imbalanced Time Series Classificationcited by 1
  26. 2026Enhancing Time Series Classification with Diversity-Driven Neural Network Ensemblescited by 1
  27. 2026CSRA: Controlled Spectral Residual Augmentation for Robust Sepsis Predictioncited by 1
  28. 2026TS2TabPFN: Time Series Classification and Extrinsic Regression through Feature Extraction and a Tabular Foundation Modelcited by 1
  29. 2024Swarm Characteristics Classification Using Neural Networkscited by 0
  30. 2025On the use of Graphs for Satellite Image Time Seriescited by 0
  31. 2025Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projectioncited by 0
  32. 2025Instruction-based Time Series Editingcited by 0
  33. 2025rETF-semiSL: Semi-Supervised Learning for Neural Collapse in Temporal Datacited by 0
  34. 2025Toward Robust Semi-supervised Regression via Dual-stream Knowledge Distillationcited by 0
  35. 2025RAxSS: Retrieval-Augmented Sparse Sampling for Explainable Variable-Length Medical Time Series Classificationcited by 0
  36. 2025STaTS: Structure-Aware Temporal Sequence Summarization via Statistical Window Mergingcited by 0
  37. 2025Robotic Classification of Divers' Swimming States using Visual Pose Keypoints as IMUscited by 0
  38. 2025When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregatecited by 0

50 most cited of 68 All 68 (JSON)