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Self-Supervised Learning (SSL) enables training performant models using limited labeled data.
The fast fourier transform
E. O. Brigham and R. E. Morrow · 1967
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Phase in speech and pictures
A. Oppenheim, Jae Lim, G. Kopec, and S. Pohlig · 1979
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The importance of phase in signals
A.V. Oppenheim and J.S. Lim · 1981
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A demonstration of the visual importance and flexibility of spatial-frequency amplitude and phase
Leon N Piotrowski and Fergus W Campbell · 1982
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Gauss and the history of the fast fourier transform
M. Heideman, D. Johnson, and C. Burrus · 1984
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Structural sparseness and spatial phase alignment in natural scenes
Bruce C Hansen and Robert F Hess · 2007
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Food-101 – mining discriminative components with random forests
Lukas Bossard, Matthieu Guillaumin, and Luc Van Gool · 2014
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dandelion Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
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Deep residual learning for image recognition, 2015
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 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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Large batch training of convolutional networks, 2017
Yang You, Igor Gitman, and Boris Ginsburg · 2017
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Places: A 10 million image database for scene recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
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Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
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The inaturalist species classification and detection dataset, 2018
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie · 2018
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Representation learning with contrastive predictive coding, 2018
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Moment matching for multi-source domain adaptation
Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, and Bo Wang · 2019
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wav2vec: Unsupervised pre-training for speech recognition
Steffen Schneider, Alexei Baevski, Ronan Collobert, and Michael Auli · 2019
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Why do self-supervised models transfer? investigating the impact of invariance on downstream tasks
Linus Ericsson, Henry G. R. Gouk, and Timothy M. Hospedales · 2021
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Masked autoencoders are scalable vision learners, 2021
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2021
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Improving transferability of representations via augmentation-aware self-supervision, 2021
Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, and Jinwoo Shin · 2021
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Learning transferable visual models from natural language supervision, 2021
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Federated self-supervised learning of multisensor representations for embedded intelligence
Aaqib Saeed, Flora D. Salim, Tanir Ozcelebi, and Johan Lukkien · 2021
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Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, and Michael Auli · 2020
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Unsupervised learning of visual features by contrasting cluster assignments, 2020
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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Exploring simple siamese representation learning, 2020
Xinlei Chen and Kaiming He · 2020
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Bootstrap your own latent: A new approach to self-supervised learning, 2020
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, and Michal Valko · 2020
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Demystifying contrastive self-supervised learning: Invariances, augmentations and dataset biases
Senthil Purushwalkam and Abhinav Kumar Gupta · 2020
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What makes for good views for contrastive learning
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, and Phillip Isola · 2020
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Fda: Fourier domain adaptation for semantic segmentation
Yanchao Yang and Stefano Soatto · 2020
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Multi-format contrastive learning of audio representations, 2021
Luyu Wang and Aaron van den Oord · 2021
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A fourier-based framework for domain generalization
Qinwei Xu, Ruipeng Zhang, Ya Zhang, Yanfeng Wang, and Qi Tian · 2021
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Barlow twins: Self-supervised learning via redundancy reduction, 2021
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
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Far: Fourier aerial video recognition, 2022
Divya Kothandaraman, Tianrui Guan, Xijun Wang, Sean Hu, Ming Lin, and Dinesh Manocha · 2022
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Self-supervised contrastive pre-training for time series via time-frequency consistency, 2022
Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, and Marinka Zitnik · 2022
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A cookbook of self-supervised learning, 2023
Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Gregoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, and Micah Goldblum · 2023
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Dinov2: Learning robust visual features without supervision, 2023
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mahmoud Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, and Piotr Bojanowski · 2023
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Augmentation-aware self-supervised learning with guided projector
Marcin Przewieźlikowski, Mateusz Pyla, Bartosz Zieli’nski, Bartlomiej Twardowski, Jacek Tabor, and Marek Śmieja · 2023
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