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Time series analysis is widely used in extensive areas.
Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the eeg
Bob Kemp, Aeilko H Zwinderman, Bert Tuk, Hilbert AC Kamphuisen, and Josefien JL Oberye · 2000
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Physionet: components of a new research resource for complex physiologic signals
PhysioToolkit PhysioBank · 2000
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Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state
Ralph G Andrzejak, Klaus Lehnertz, Florian Mormann, Christoph Rieke, Peter David, and Christian E Elger · 2001
Earlier work this paper cites.
uwave: Accelerometer-based personalized gesture recognition and its applications
Jiayang Liu, Lin Zhong, Jehan Wickramasuriya, and Venu Vasudevan · 2009
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
Pascal Vincent, H. Larochelle, Isabelle Lajoie, Yoshua Bengio, and Pierre-Antoine Manzagol · 2010
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Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin · 2015
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Deep residual learning for image recognition
Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun · 2016
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Condition monitoring of bearing damage in electromechanical drive systems by using motor current signals of electric motors: A benchmark data set for data-driven classification
Christian Lessmeier, James Kuria Kimotho, Detmar Zimmer, and Walter Sextro · 2016
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Extracting optimal performance from dynamic time warping
Abdullah Al Mueen and Eamonn J. Keogh · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
Alex Kendall, Yarin Gal, and Roberto Cipolla · 2018
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Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X. Yu, and Dahua Lin · 2018
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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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Similarity of neural network representations revisited
Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey E. Hinton · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, S. Gross, Francisco Massa, A. Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Z. Lin, N. Gimelshein, L. Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
Cited alongside, same era.
Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen · 2020
Cited alongside, same era.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Cited alongside, same era.
A survey on contrastive self-supervised learning
Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Debapriya Banerjee, and Fillia Makedon · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J Liu, et al · 2020
Cited alongside, same era.
Self-supervised learning for ecg-based emotion recognition
Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Transferability in deep learning: A survey
Junguang Jiang, Yang Shu, Jianmin Wang, and Mingsheng Long · 2022
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Non-stationary transformers: Exploring the stationarity in time series forecasting
Yong Liu, Haixu Wu, Jianmin Wang, and Mingsheng Long · 2022
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Utilizing expert features for contrastive learning of time-series representations
Manuel T Nonnenmacher, Lukas Oldenburg, Ingo Steinwart, and David Reeb · 2022
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Learning latent seasonal-trend representations for time series forecasting
Zhiyuan Wang, Xovee Xu, Weifeng Zhang, Goce Trajcevski, Ting Zhong, and Fan Zhou · 2022
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Pritam Sarkar and Ali Etemad · 2020
Cited alongside, same era.
Exploring contrastive learning in human activity recognition for healthcare
Chi Ian Tang, Ignacio Perez-Pozuelo, Dimitris Spathis, and Cecilia Mascolo · 2020
Cited alongside, same era.
Understanding contrastive representation learning through alignment and uniformity on the hypersphere
Tongzhou Wang and Phillip Isola · 2020
Cited alongside, same era.
Time-series representation learning via temporal and contextual contrasting
Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, and Cuntai Guan · 2021
Cited alongside, same era.
Self-supervised learning: Generative or contrastive
Xiao Liu, Fanjin Zhang, Zhenyu Hou, Li Mian, Zhaoyu Wang, Jing Zhang, and Jie Tang · 2021
Cited alongside, same era.
Online false discovery rate control for anomaly detection in time series
Quentin Rebjock, Baris Kurt, Tim Januschowski, and Laurent Callot · 2021
Cited alongside, same era.
Adjusting for autocorrelated errors in neural networks for time series
Fan-Keng Sun, Chris Lang, and Duane Boning · 2021
Cited alongside, same era.
Mixing up contrastive learning: Self-supervised representation learning for time series
Kristoffer Wickstrøm, Michael Kampffmeyer, Karl Øyvind Mikalsen, and Robert Jenssen · 2022
Later among the works it cites.
Cost: Contrastive learning of disentangled seasonal-trend representations for time series forecasting
Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, and Steven Hoi · 2022
Later among the works it cites.
Simmim: A simple framework for masked image modeling
Zhenda Xie, Zheng Zhang, Yue Cao, Yutong Lin, Jianmin Bao, Zhuliang Yao, Qi Dai, and Han Hu · 2022
Later among the works it cites.
Unsupervised time-series representation learning with iterative bilinear temporal-spectral fusion
Ling Yang and Shenda Hong · 2022
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Timeclr: A self-supervised contrastive learning framework for univariate time series representation
Xinyu Yang, Zhenguo Zhang, and Rongyi Cui · 2022
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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
Later among the works it cites.
Self-supervised contrastive pre-training for time series via time-frequency consistency
Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, and Marinka Zitnik · 2022
Later among the works it cites.
Timemae: Self-supervised representations of time series with decoupled masked autoencoders
Mingyue Cheng, Qi Liu, Zhiding Liu, Hao Zhang, Rujiao Zhang, and Enhong Chen · 2023
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Scaling language-image pre-training via masking
Yanghao Li, Haoqi Fan, Ronghang Hu, Christoph Feichtenhofer, and Kaiming He · 2023
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Ti-mae: Self-supervised masked time series autoencoders
Zhe Li, Zhongwen Rao, Lujia Pan, Pengyun Wang, and Zenglin Xu · 2023
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A time series is worth 64 words: Long-term forecasting with transformers
Yuqi Nie, Nam H Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam · 2023
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Should you mask 15% in masked language modeling?
Alexander Wettig, Tianyu Gao, Zexuan Zhong, and Danqi Chen · 2023
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Revealing the dark secrets of masked image modeling
Zhenda Xie, Zigang Geng, Jingcheng Hu, Zheng Zhang, Han Hu, and Yue Cao · 2023
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