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Time-series representation learning can extract representations from data with temporal dynamics and sparse labels.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Time-series data mining
Philippe Esling and Carlos Agon · 2012
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A public domain dataset for human activity recognition using smartphones
Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra Perez, and Jorge Luis Reyes Ortiz · 2013
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Dtw-d: time series semi-supervised learning from a single example
Yanping Chen, Bing Hu, Eamonn Keogh, and Gustavo EAPA Batista · 2013
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Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
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Discriminative unsupervised feature learning with exemplar convolutional neural networks
Dosovitskiy Alexey, Philipp Fischer, Jost Tobias, Martin Riedmiller Springenberg, and Thomas Brox · 2015
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
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Unsupervised deep embedding for clustering analysis
Junyuan Xie, Ross Girshick, and Ali Farhadi · 2016
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Colorization as a proxy task for visual understanding
Gustav Larsson, Michael Maire, and Gregory Shakhnarovich · 2017
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Split-brain autoencoders: Unsupervised learning by cross-channel prediction
Richard Zhang, Phillip Isola, and Alexei A Efros · 2017
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Unsupervised learning by predicting noise
Piotr Bojanowski and Armand Joulin · 2017
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Representation learning by learning to count
Mehdi Noroozi, Hamed Pirsiavash, and Paolo Favaro · 2017
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Multi-task self-supervised visual learning
Carl Doersch and Andrew Zisserman · 2017
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Learning features by watching objects move
Deepak Pathak, Ross Girshick, Piotr Dollár, Trevor Darrell, and Bharath Hariharan · 2017
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Anomaly detection in streams with extreme value theory
Alban Siffer, Pierre-Alain Fouque, Alexandre Termier, and Christine Largouet · 2017
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Speeding up similarity search under dynamic time warping by pruning unpromising alignments
Diego F Silva, Rafael Giusti, Eamonn Keogh, and Gustavo EAPA Batista · 2018
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Opportunities and obstacles for deep learning in biology and medicine
Travers Ching, Daniel S Himmelstein, Brett K Beaulieu-Jones, Alexandr A Kalinin, Brian T Do, Gregory P Way, Enrico Ferrero, Paul-Michael Agapow, Michael Zietz, Michael M Hoffman, et al · 2018
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Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
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Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze · 2018
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Time series data augmentation for deep learning: A survey
Qingsong Wen, Liang Sun, Fan Yang, Xiaomin Song, Jingkun Gao, Xue Wang, and Huan Xu · 2020
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A survey on contrastive self-supervised learning
Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Debapriya Banerjee, and Fillia Makedon · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, et al · 2020
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Mehdi Noroozi, Ananth Vinjimoor, Paolo Favaro, and Hamed Pirsiavash · 2018
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The uea multivariate time series classification archive, 2018
Anthony Bagnall, Hoang Anh Dau, Jason Lines, Michael Flynn, James Large, Aaron Bostrom, Paul Southam, and Eamonn Keogh · 2018
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Modeling long-and short-term temporal patterns with deep neural networks
Guokun Lai, Wei-Cheng Chang, Yiming Yang, and Hanxiao Liu · 2018
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An empirical evaluation of generic convolutional and recurrent networks for sequence modeling
Shaojie Bai, J Zico Kolter, and Vladlen Koltun · 2018
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Unsupervised anomaly detection via variational auto-encoder for seasonal kpis in web applications
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A mutual information maximization perspective of language representation learning
Lingpeng Kong, Cyprien de Masson d’Autume, Wang Ling, Lei Yu, Zihang Dai, and Dani Yogatama · 2019
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Unsupervised scalable representation learning for multivariate time series
Jean-Yves Franceschi, Aymeric Dieuleveut, and Martin Jaggi · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Multi-task self-supervised learning for disfluency detection
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Multi-task self-supervised learning for robust speech recognition
Mirco Ravanelli, Jianyuan Zhong, Santiago Pascual, Pawel Swietojanski, Joao Monteiro, Jan Trmal, and Yoshua Bengio · 2020
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Spectral temporal graph neural network for multivariate time-series forecasting
Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Congrui Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, et al · 2020
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Self-guided contrastive learning for bert sentence representations
Taeuk Kim, Kang Min Yoo, and Sang-goo Lee · 2021
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A simple and effective self-supervised contrastive learning framework for aspect detection
Tian Shi, Liuqing Li, Ping Wang, and Chandan K Reddy · 2021
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Unsupervised representation learning for time series with temporal neighborhood coding
Sana Tonekaboni, Danny Eytan, and Anna Goldenberg · 2021
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A transformer-based framework for multivariate time series representation learning
George Zerveas, Srideepika Jayaraman, Dhaval Patel, Anuradha Bhamidipaty, and Carsten Eickhoff · 2021
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Time-series representation learning via temporal and contextual contrasting
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Sit: Self-supervised vision transformer
Sara Atito, Muhammad Awais, and Josef Kittler · 2021
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Informer: Beyond efficient transformer for long sequence time-series forecasting
Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, and Wancai Zhang · 2021
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Ts2vec: Towards universal representation of time series
Zhihan Yue, Yujing Wang, Juanyong Duan, Tianmeng Yang, Congrui Huang, Yunhai Tong, and Bixiong Xu · 2022
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