{"total":46,"rows":[{"id":"2104.07551","title":"HIVE-COTE 2.0: a new meta ensemble for time series classification","created":"2021-04-15","cited_by_count":118,"area":null},{"id":"2304.13029","title":"Bake off redux: a review and experimental evaluation of recent time series classification algorithms","created":"2023-04-25","cited_by_count":101,"area":null},{"id":"2102.00457","title":"MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification","created":"2021-01-31","cited_by_count":90,"area":null},{"id":"2302.02515","title":"Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey","created":"2023-02-06","cited_by_count":68,"area":null},{"id":"2203.13652","title":"HYDRA: Competing convolutional kernels for fast and accurate time series classification","created":"2022-03-25","cited_by_count":54,"area":null},{"id":"2406.14231","title":"aeon: a Python toolkit for learning from time series","created":"2024-06-20","cited_by_count":47,"area":null},{"id":"2305.11921","title":"An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Set","created":"2023-05-19","cited_by_count":29,"area":null},{"id":"2212.09840","title":"Dynamic Sparse Network for Time Series Classification: Learning What to \"see''","created":"2022-12-19","cited_by_count":22,"area":null},{"id":"2308.00928","title":"QUANT: A Minimalist Interval Method for Time Series Classification","created":"2023-08-02","cited_by_count":15,"area":null},{"id":"2207.12165","title":"dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification","created":"2022-07-25","cited_by_count":11,"area":null},{"id":"2409.02869","title":"Look Into the LITE in Deep Learning for Time Series Classification","created":"2024-09-04","cited_by_count":9,"area":null},{"id":"2102.10231","title":"Elastic Similarity and Distance Measures for Multivariate Time Series","created":"2021-02-20","cited_by_count":8,"area":null},{"id":"2109.12094","title":"A spatiotemporal machine learning approach to forecasting COVID-19 incidence at the county level in the USA","created":"2021-09-24","cited_by_count":7,"area":null},{"id":"2203.03445","title":"S-Rocket: Selective Random Convolution Kernels for Time Series Classification","created":"2022-03-07","cited_by_count":7,"area":null},{"id":"2310.02812","title":"Time-Series Classification in Smart Manufacturing Systems: An Experimental Evaluation of State-of-the-Art Machine Learning Algorithms","created":"2023-10-04","cited_by_count":7,"area":null},{"id":"2502.15122","title":"MONSTER: Monash Scalable Time Series Evaluation Repository","created":"2025-02-21","cited_by_count":6,"area":null},{"id":"2105.14876","title":"Fast, Accurate and Interpretable Time Series Classification Through Randomization","created":"2021-05-31","cited_by_count":5,"area":null},{"id":"2207.07564","title":"Rethinking Attention Mechanism in Time Series Classification","created":"2022-07-14","cited_by_count":5,"area":null},{"id":"2304.05800","title":"Proximity Forest 2.0: A new effective and scalable similarity-based classifier for time series","created":"2023-04-12","cited_by_count":5,"area":null},{"id":"2309.08499","title":"POCKET: Pruning Random Convolution Kernels for Time Series Classification from a Feature Selection Perspective","created":"2023-09-15","cited_by_count":5,"area":null},{"id":"2403.04882","title":"Efficient High-Resolution Time Series Classification via Attention Kronecker Decomposition","created":"2024-03-07","cited_by_count":5,"area":null},{"id":"2102.04179","title":"Plotting time: On the usage of CNNs for time series classification","created":"2021-02-08","cited_by_count":3,"area":null},{"id":"2102.05221","title":"Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warping","created":"2021-02-10","cited_by_count":3,"area":null},{"id":"2301.10350","title":"Parameterizing the cost function of Dynamic Time Warping with application to time series classification","created":"2023-01-24","cited_by_count":3,"area":null},{"id":"2410.03098","title":"Forest Proximities for Time Series","created":"2024-10-04","cited_by_count":3,"area":null},{"id":"2111.13314","title":"Amercing: An Intuitive, Elegant and Effective Constraint for Dynamic Time Warping","created":"2021-11-26","cited_by_count":2,"area":null},{"id":"2406.14456","title":"Capturing Temporal Components for Time Series Classification","created":"2024-06-20","cited_by_count":2,"area":null},{"id":"2302.06683","title":"Enhancing Multivariate Time Series Classifiers through Self-Attention and Relative Positioning Infusion","created":"2023-02-13","cited_by_count":1,"area":null},{"id":"2306.10084","title":"Convolutional and Deep Learning based techniques for Time Series Ordinal Classification","created":"2023-06-16","cited_by_count":1,"area":null},{"id":"2311.14549","title":"FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification","created":"2023-11-24","cited_by_count":1,"area":null},{"id":"2407.00843","title":"A Unified Approach to Extract Interpretable Rules from Tree Ensembles via Integer Programming","created":"2024-06-30","cited_by_count":1,"area":null},{"id":"2504.03318","title":"Adaptive Classification of Interval-Valued Time Series","created":"2025-04-04","cited_by_count":1,"area":null},{"id":"2509.22919","title":"Label-Guided Imputation via Forest-Based Proximities for Improved Time Series Classification","created":"2025-09-26","cited_by_count":1,"area":null},{"id":"2512.12076","title":"SigTime: Learning and Visually Explaining Time Series Signatures","created":"2025-12-12","cited_by_count":1,"area":null},{"id":"2602.07579","title":"Enhancing Time Series Classification with Diversity-Driven Neural Network Ensembles","created":"2026-02-07","cited_by_count":1,"area":null},{"id":"2607.19234","title":"In-Context Time Series Classification with Random Convolutional Features","created":"2026-07-21","cited_by_count":1,"area":null},{"id":"2207.03119","title":"Semi-unsupervised Learning for Time Series Classification","created":"2022-07-07","cited_by_count":0,"area":null},{"id":"2305.00465","title":"New bootstrap tests for categorical time series. A comparative study","created":"2023-04-30","cited_by_count":0,"area":null},{"id":"2308.13968","title":"Multivariate time series classification with dual attention network","created":"2023-08-26","cited_by_count":0,"area":null},{"id":"2407.14735","title":"ECRTime: Ensemble Integration of Classification and Retrieval for Time Series Classification","created":"2024-07-20","cited_by_count":0,"area":null},{"id":"2409.08636","title":"Utilizing Data Fingerprints for Privacy-Preserving Algorithm Selection in Time Series Classification: Performance and Uncertainty Estimation on Unseen Datasets","created":"2024-09-13","cited_by_count":0,"area":null},{"id":"2503.16938","title":"Interpretable Machine Learning for Oral Lesion Diagnosis through Prototypical Instances Identification","created":"2025-03-21","cited_by_count":0,"area":null},{"id":"2504.04667","title":"Interval-Valued Time Series Classification Using $D_K$-Distance","created":"2025-04-07","cited_by_count":0,"area":null},{"id":"2511.19487","title":"The Generalized Proximity Forest","created":"2025-11-23","cited_by_count":0,"area":null},{"id":"2602.12744","title":"Adaptive Structured Pruning of Convolutional Neural Networks for Time Series Classification","created":"2026-02-13","cited_by_count":0,"area":null},{"id":"2609.02203","title":"SMart: A Multi-source Multi-phase Time Series Representation Transfer Framework","created":"2026-09-02","cited_by_count":0,"area":null}],"next_cursor":null}