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This paper presents TS2Vec, a universal framework for learning representations of time series in an arbitrary semantic level.
Statistical comparisons of classifiers over multiple data sets
Demšar, J. 2006 · 2006
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Network anomaly detection based on wavelet analysis
Lu, W.; and Ghorbani, A. A. 2008 · 2009
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Fourier transform based spatial outlier mining
Rasheed, F.; Peng, P.; Alhajj, R.; and Rokne, J. 2009 · 2009
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Rapid detection of maintenance induced changes in service performance
Mahimkar, A.; Ge, Z.; Wang, J.; Yates, J.; Zhang, Y.; Emmons, J.; Huntley, B.; and Stockert, M. 2011 · 2011
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Hierarchical Semantic Aggregation for Contrastive Representation Learning
Xu, H.; Zhang, X.; Li, H.; Xie, L.; Xiong, H.; and Tian, Q. 2020 · 2012
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DTW-D: time series semi-supervised learning from a single example
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Stock price prediction using the ARIMA model
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Box, G. E.; Jenkins, G. M.; Reinsel, G. C.; and Ljung, G. M. 2015 · 2015
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A Benchmark Dataset for Time Series Anomaly Detection
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UCI Machine Learning Repository
Dua, D.; and Graff, C. 2017 · 2017
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TimeNet: Pre-trained deep recurrent neural network for time series classification
Malhotra, P.; TV, V.; Vig, L.; Agarwal, P.; and Shroff, G. 2017 · 2017
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Anomaly detection in streams with extreme value theory
Siffer, A.; Fouque, P.-A.; Termier, A.; and Largouet, C. 2017 · 2017
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A multi-horizon quantile recurrent forecaster
Wen, R.; Torkkola, K.; Narayanaswamy, B.; and Madeka, D. 2017 · 2017
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The UEA multivariate time series classification archive, 2018
Bagnall, A. J.; Dau, H. A.; Lines, J.; Flynn, M.; Large, J.; Bostrom, A.; Southam, P.; and Keogh, E. J. 2018 · 2018
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An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
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Luminol (GitHub repository)
Brennan, V.; and Ritesh, M. 2018 · 2018
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Lai, G.; Chang, W.-C.; Yang, Y.; and Liu, H. 2018 · 2018
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An efficient framework for learning sentence representations
Logeswaran, L.; and Lee, H. 2018 · 2018
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Wan, R.; Mei, S.; Wang, J.; Liu, M.; and Yang, F. 2019 · 2019
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wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
Baevski, A.; Zhou, Y.; Mohamed, A.; and Auli, M. 2020 · 2020
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Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
Cao, D.; Wang, Y.; Duan, J.; Zhang, C.; Zhu, X.; Huang, C.; Tong, Y.; Xu, B.; Bai, J.; Tong, J.; and Zhang, Q. 2020 · 2020
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A simple framework for contrastive learning of visual representations
Chen, T.; Kornblith, S.; Norouzi, M.; and Hinton, G. 2020 · 2020
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On translation invariance in cnns: Convolutional layers can exploit absolute spatial location
Kayhan, O. S.; and Gemert, J. C. v. 2020 · 2020
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Unsupervised anomaly detection via variational auto-encoder for seasonal kpis in web applications
Xu, H.; Chen, W.; Zhao, N.; Li, Z.; Bu, J.; Li, Z.; Liu, Y.; Zhao, Y.; Pei, D.; Feng, Y.; et al. 2018 · 2018
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The UCR time series archive
Dau, H. A.; Bagnall, A.; Kamgar, K.; Yeh, C.-C. M.; Zhu, Y.; Gharghabi, S.; Ratanamahatana, C. A.; and Keogh, E. 2019 · 2019
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Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
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Unsupervised Learning of Dense Visual Representations
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Salinas, D.; Flunkert, V.; Gasthaus, J.; and Januschowski, T. 2020 · 2020
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Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Zhou, H.; Zhang, S.; Peng, J.; Zhang, S.; Li, J.; Xiong, H.; and Zhang, W. 2021 · 2020
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Time-Series Representation Learning via Temporal and Contextual Contrasting
Eldele, E.; Ragab, M.; Chen, Z.; Wu, M.; Kwoh, C. K.; Li, X.; and Guan, C. 2021 · 2021
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SimCSE: Simple Contrastive Learning of Sentence Embeddings
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Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
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Dense Contrastive Learning for Self-Supervised Visual Pre-Training
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Self-training and Pre-training are Complementary for Speech Recognition
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