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Neural Collapse (NC) gives a precise description of the representations of classes in the final hidden layer of classification neural networks.
Vardan Papyan · 1901
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“The MNIST database of handwritten digits”
Yann LeCun · 1998
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“Learning multiple layers of features from tiny images”
Alex Krizhevsky and Geoffrey Hinton · 2009
Earlier work this paper cites.
“Neural collapse with unconstrained features”
Dustin. Mixon, Hans Parshall and Jianzong Pi · 2011
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“Reading digits in natural images with unsupervised feature learning”, 2011
Yuval Netzer et al · 2011
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“Neural Collapse with Cross-Entropy Loss”
Jianfeng Lu and Stefan Steinerberger · 2012
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“Very Deep Convolutional Networks for Large-Scale Image Recognition”
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
“Very deep convolutional networks for large-scale image recognition”
Karen Simonyan and Andrew Zisserman · 2014
Cited alongside, same era.
“Deep learning”
Yann LeCun, Yoshua Bengio and Geoffrey Hinton · 2015
Cited alongside, same era.
“Deep learning”
Ian Goodfellow, Yoshua Bengio and Aaron Courville · 2016
Cited alongside, same era.
“Imagenet classification with deep convolutional neural networks”
Alex Krizhevsky, Ilya Sutskever and Geoffrey Hinton · 2017
Cited alongside, same era.
“Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms”
Han Xiao, Kashif Rasul and Roland Vollgraf · 2017
Cited alongside, same era.
“Super-Convergence: Very Fast Training of Neural Networks Using Large Learning Rates”, 2018
“Revealing the structure of deep neural networks via convex duality”
Tolga Ergen and Mert Pilanci · 2021
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“Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training”
Cong Fang, Hangfeng He, Qi Long and Weijie Su · 2021
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“A geometric analysis of neural collapse with unconstrained features”
Zhihui Zhu et al · 2021
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“Neural collapse under mse loss: Proximity to and dynamics on the central path”
XY Han, Vardan Papyan and David Donoho · 2021
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“Extended Unconstrained Features Model for Exploring Deep Neural Collapse”
Tom Tirer and Joan Bruna · 2022
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“Are All Losses Created Equal: A Neural Collapse Perspective”
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Leslie. Smith and Nicholay Topin · 2018
Cited alongside, same era.
“Prevalence of neural collapse during the terminal phase of deep learning training”
Vardan Papyan, XY Han and David Donoho · 2020
Cited alongside, same era.
Jinxin Zhou et al · 2022
Later among the works it cites.