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Multivariate time series classification (MTSC) has attracted significant research attention due to its diverse real-world applications.
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The BOSS is concerned with time series classification in the presence of noise
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Attention is all you need
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Multivariate LSTM-FCNs for time series classification
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Multivariate LSTM-FCNs for time series classification
Fazle Karim, Somshubra Majumdar, Houshang Darabi, and Samuel Harford. 2019b · 2019
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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, and Anthony Bagnall. 2021a · 2021
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The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances
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A transformer-based framework for multivariate time series representation learning. In Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining . 2114–2124
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A reinforcement learning-informed pattern mining framework for multivariate time series classification. In In the Proceeding of 31th International Joint Conference on Artificial Intelligence (IJCAI-22)
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Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep
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A novel non-parametric method for time series classification based on k-Nearest Neighbors and Dynamic Time Warping Barycenter Averaging
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An image is worth 16x16 words: Transformers for image recognition at scale
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A new attention mechanism to classify multivariate time series. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
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An improvement of SAX representation for time series by using complexity invariance
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Semi-supervised collaborative filtering by text-enhanced domain adaptation. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 2136–2144
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Learning Perceptual Position-Aware Shapelets for Time Series Classification. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases . Springer, 53–69
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A time series is worth 64 words: Long-term forecasting with transformers
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MultiRocket: multiple pooling operators and transformations for fast and effective time series classification
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Timesnet: Temporal 2d-variation modeling for general time series analysis. In The eleventh international conference on learning representations
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Ts2vec: Towards universal representation of time series. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 36. 8980–8987
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Improving Position Encoding of Transformers for Multivariate Time Series Classification
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NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation
Minh-Tuan Tran, Trung Le, Xuan-May Le, Mehrtash Harandi, Quan Hung Tran, and Dinh Phung. 2023 · 2023
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WHEN: A Wavelet-DTW Hybrid Attention Network for Heterogeneous Time Series Analysis. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 2361–2373
Jingyuan Wang, Chen Yang, Xiaohan Jiang, and Junjie Wu. 2023 · 2023
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Revisiting citation prediction with cluster-aware text-enhanced heterogeneous graph neural networks. In 2023 IEEE 39th International Conference on Data Engineering (ICDE) . IEEE, 682–695
Carl Yang and Jiawei Han. 2023 · 2023
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One fits all: Power general time series analysis by pretrained lm
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SVP-T: a shape-level variable-position transformer for multivariate time series classification. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 37. 11497–11505
Rundong Zuo, Guozhong Li, Byron Choi, Sourav S Bhowmick, Daphne Ngar-yin Mah, and Grace LH Wong. 2023 · 2023
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Text-Enhanced Data-free Approach for Federated Class-Incremental Learning
Minh-Tuan Tran, Trung Le, Xuan-May Le, Mehrtash Harandi, and Dinh Phung. 2024 · 2024
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