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Leveraging multimodal information from biosignals is vital for building a comprehensive representation of people's physical and mental states.
Experimental studies on 1/f noise
FN Hooge, TGM Kleinpenning, and Lode KJ Vandamme · 1981
Earlier work this paper cites.
The fast Fourier transform and its applications
E Oran Brigham · 1988
Earlier work this paper cites.
Category learning through multimodality sensing
Virginia R De Sa and Dana H Ballard · 1998
Earlier work this paper cites.
Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals
Ary L Goldberger, Luis AN Amaral, Leon Glass, Jeffrey M Hausdorff, Plamen Ch Ivanov, Roger G Mark, Joseph E Mietus, George B Moody, Chung-Kang Peng, and H Eugene Stanley · 2000
Earlier work this paper cites.
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
Earlier work this paper cites.
Digital image processing algorithms and applications
Ioannis Pitas · 2000
Earlier work this paper cites.
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.
The development of embodied cognition: Six lessons from babies
Linda Smith and Michael Gasser · 2005
Earlier work this paper cites.
Distinguishing low frequency oscillations within the 1/f spectral behaviour of electromagnetic brain signals
Charmaine Demanuele, Christopher J James, and Edmund JS Sonuga-Barke · 2007
Earlier work this paper cites.
Fourier neural operator for parametric partial differential equations
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, and Anima Anandkumar · 2010
Earlier work this paper cites.
Real-time eeg-based human emotion recognition and visualization
Yisi Liu, Olga Sourina, and Minh Khoa Nguyen · 2010
Earlier work this paper cites.
Eeg signal analysis: a survey
D Puthankattil Subha, Paul K Joseph, Rajendra Acharya U, and Choo Min Lim · 2010
Earlier work this paper cites.
Multimodal biosignal sensor data handling for emotion recognition
Filipe Canento, Ana Fred, Hugo Silva, Hugo Gamboa, and André Lourenço · 2011
Earlier work this paper cites.
Hypernetworks
Ha David, Dai Andrew, and VL Quoc · 2016
Earlier work this paper cites.
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
Earlier work this paper cites.
A generalized convolution theorem for the special affine fourier transform and its application to filtering
Xiyang Zhi, Deyun Wei, and Wei Zhang · 2016
Earlier work this paper cites.
Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
Earlier work this paper cites.
Deepsleepnet: A model for automatic sleep stage scoring based on raw single-channel eeg
Akara Supratak, Hao Dong, Chao Wu, and Yike Guo · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
Review on psychological stress detection using biosignals
Giorgos Giannakakis, Dimitris Grigoriadis, Katerina Giannakaki, Olympia Simantiraki, Alexandros Roniotis, and Manolis Tsiknakis · 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
Cited alongside, same era.
Stfnets: Learning sensing signals from the time-frequency perspective with short-time fourier neural networks
Shuochao Yao, Ailing Piao, Wenjun Jiang, Yiran Zhao, Huajie Shao, Shengzhong Liu, Dongxin Liu, Jinyang Li, Tianshi Wang, Shaohan Hu, et al · 2019
Cited alongside, same era.
Cross-domain mlp and cnn transfer learning for biological signal processing: Eeg and emg
Jordan J Bird, Jhonatan Kobylarz, Diego R Faria, Anikó Ekárt, and Eduardo P Ribeiro · 2020
Cited alongside, same era.
Subject-aware contrastive learning for biosignals
Joseph Y Cheng, Hanlin Goh, Kaan Dogrusoz, Oncel Tuzel, and Erdrin Azemi · 2020
Deep vision multimodal learning: Methodology, benchmark, and trend
Wenhao Chai and Gaoang Wang · 2022
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Maeeg: Masked auto-encoder for eeg representation learning
Hsiang-Yun Sherry Chien, Hanlin Goh, Christopher M Sandino, and Joseph Y Cheng · 2022
Later among the works it cites.
Self-supervised representation learning: Introduction, advances, and challenges
Linus Ericsson, Henry Gouk, Chen Change Loy, and Timothy M Hospedales · 2022
Later among the works it cites.
Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Paul Pu Liang, Amir Zadeh, and Louis-Philippe Morency · 2022
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Parameterizing neural power spectra into periodic and aperiodic components
Thomas Donoghue, Matar Haller, Erik J Peterson, Paroma Varma, Priyadarshini Sebastian, Richard Gao, Torben Noto, Antonio H Lara, Joni D Wallis, Robert T Knight, et al · 2020
Cited alongside, same era.
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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Vatt: Transformers for multimodal self-supervised learning from raw video, audio and text
Hassan Akbari, Liangzhe Yuan, Rui Qian, Wei-Hong Chuang, Shih-Fu Chang, Yin Cui, and Boqing Gong · 2021
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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
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Efficiently modeling long sequences with structured state spaces
Albert Gu, Karan Goel, and Christopher Ré · 2021
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Adaptive fourier neural operators: Efficient token mixers for transformers
John Guibas, Morteza Mardani, Zongyi Li, Andrew Tao, Anima Anandkumar, and Bryan Catanzaro · 2021
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What makes multi-modal learning better than single (provably)
Yu Huang, Chenzhuang Du, Zihui Xue, Xuanyao Chen, Hang Zhao, and Longbo Huang · 2021
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Unified-io: A unified model for vision, language, and multi-modal tasks
Jiasen Lu, Christopher Clark, Rowan Zellers, Roozbeh Mottaghi, and Aniruddha Kembhavi · 2022
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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 · 2022
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Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, et al · 2022
Later among the works it cites.
Ofa: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework
Peng Wang, An Yang, Rui Men, Junyang Lin, Shuai Bai, Zhikang Li, Jianxin Ma, Chang Zhou, Jingren Zhou, and Hongxia Yang · 2022
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Mixing up contrastive learning: Self-supervised representation learning for time series
Kristoffer Wickstrøm, Michael Kampffmeyer, Karl Øyvind Mikalsen, and Robert Jenssen · 2022
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neuro2vec: Masked fourier spectrum prediction for neurophysiological representation learning
Di Wu, Siyuan Li, Jie Yang, and Mohamad Sawan · 2022
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Masked frequency modeling for self-supervised visual pre-training
Jiahao Xie, Wei Li, Xiaohang Zhan, Ziwei Liu, Yew Soon Ong, and Chen Change Loy · 2022
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Unsupervised time-series representation learning with iterative bilinear temporal-spectral fusion
Ling Yang and Shenda Hong · 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
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Simmtm: A simple pre-training framework for masked time-series modeling
Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, and Mingsheng Long · 2023
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Lu Han, Han-Jia Ye, and De-Chuan Zhan · 2023
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Robustness in multimodal learning under train-test modality mismatch
Brandon McKinzie, Vaishaal Shankar, Joseph Yitan Cheng, Yinfei Yang, Jonathon Shlens, and Alexander T Toshev · 2023
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Hiera: A hierarchical vision transformer without the bells-and-whistles
Chaitanya Ryali, Yuan-Ting Hu, Daniel Bolya, Chen Wei, Haoqi Fan, Po-Yao Huang, Vaibhav Aggarwal, Arkabandhu Chowdhury, Omid Poursaeed, Judy Hoffman, et al · 2023
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