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Current state-of-the-art deep networks are all powered by backpropagation.
Momentum Contrast for Unsupervised Visual Representation Learning, March 2020
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 1911
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Mental rotation of three-dimensional objects
Roger N. Shepard and Jacqueline Metzler · 1971
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Improved Baselines with Momentum Contrastive Learning, March 2020c
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2003
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Extreme learning machine: a new learning scheme of feedforward neural networks
Guang-Bin Huang, Qin-Yu Zhu, and Chee-Kheong Siew · 2004
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Greedy layer-wise training of deep networks
Yoshua Bengio, Pascal Lamblin, Dan Popovici, and Hugo Larochelle · 2006
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Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, January 2021a
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2006
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Big Self-Supervised Models are Strong Semi-Supervised Learners, October 2020b
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey Hinton · 2006
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A fast learning algorithm for deep belief nets
Geoffrey E Hinton, Simon Osindero, and Yee-Whye Teh · 2006
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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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Deep boltzmann machines
Ruslan Salakhutdinov and Geoffrey Hinton · 2009
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Difference target propagation
Dong-Hyun Lee, Saizheng Zhang, Asja Fischer, and Yoshua Bengio · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Direct feedback alignment provides learning in deep neural networks
Arild Nøkland · 2016
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Greedy layerwise learning can scale to ImageNet
Eugene Belilovsky, Michael Eickenberg, and Edouard Oyallon · 2019
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Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2019
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Putting an end to end-to-end: Gradient-isolated learning of representations
Sindy Löwe, Peter O’Connor, and Bastiaan S Veeling · 2019
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Gait-prop: A biologically plausible learning rule derived from backpropagation of error
Nasir Ahmad, Marcel A. J. van Gerven, and Luca Ambrogioni · 2020
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Greedy hierarchical variational autoencoders for large-scale video prediction
Bohan Wu, Suraj Nair, Roberto Martin-Martin, Li Fei-Fei, and Chelsea Finn · 2021
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Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
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VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, January 2022
Adrien Bardes, Jean Ponce, and Yann LeCun · 2022
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Towards scaling difference target propagation by learning backprop targets
Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake Richards, and Yoshua Bengio · 2022
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The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks, March 2022
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Backpropagation and the brain
Timothy P. Lillicrap, Adam Santoro, Luke Marris, Colin J. Akerman, and Geoffrey Hinton · 2020
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Loco: Local contrastive representation learning
Yuwen Xiong, Mengye Ren, and Raquel Urtasun · 2020
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Deep Learning Through the Lens of Example Difficulty
Robert Baldock, Hartmut Maennel, and Behnam Neyshabur · 2021
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Credit Assignment Through Broadcasting a Global Error Vector
David Clark, L F Abbott, and Sueyeon Chung · 2021
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Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson, Pierre Sermanet, and Andrew Zisserman · 2021
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Local plasticity rules can learn deep representations using self-supervised contrastive predictions
Bernd Illing, Jean Ventura, Guillaume Bellec, and Wulfram Gerstner · 2021
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Manu S. Halvagal and Friedemann Zenke · 2022
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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The forward-forward algorithm: Some preliminary investigations
Geoffrey Hinton · 2022
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Hebbian deep learning without feedback
Adrien Journé, Hector Garcia Rodriguez, Qinghai Guo, and Timoleon Moraitis · 2022
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Biologically plausible training mechanisms for self-supervised learning in deep networks
Mufeng Tang, Yibo Yang, and Yali Amit · 2022
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A-ViT: Adaptive Tokens for Efficient Vision Transformer, March 2022
Hongxu Yin, Arash Vahdat, Jose Alvarez, Arun Mallya, Jan Kautz, and Pavlo Molchanov · 2022
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Random synaptic feedback weights support error backpropagation for deep learning
Timothy P. Lillicrap, Daniel Cownden, Douglas B. Tweed, and Colin J. Akerman · 2041
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