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Neural Collapse: A Review on Modelling Principles and Generalization

8 June 2022

Papers citing "Neural Collapse: A Review on Modelling Principles and Generalization"

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Title
Open-Set Semi-Supervised Learning for Long-Tailed Medical Datasets Daniya Najiha Abdul Kareem Jean Lahoud Mustansar Fiaz Amandeep Kumar Hisham Cholakkal OOD 147 0 0 20 May 2025
The Spotlight Resonance Method: Resolving the Alignment of Embedded Activations George Bird 57 0 0 09 May 2025
Robust Weight Imprinting: Insights from Neural Collapse and Proxy-Based Aggregation Justus Westerhoff Golzar Atefi Mario Koddenbrock Alexei Figueroa Alexander Loser Erik Rodner Felix Alexader Gers OffRL 102 0 0 18 Mar 2025
Formation of Representations in Neural Networks Liu Ziyin Isaac Chuang Tomer Galanti T. Poggio 206 7 0 03 Oct 2024
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection Yingwen Wu Ruiji Yu Xinwen Cheng Zhengbao He Xiaolin Huang OODD 96 3 0 28 May 2024
Maximally Compact and Separated Features with Regular Polytope Networks F. Pernici Matteo Bruni C. Baecchi A. Bimbo 75 19 0 15 Jan 2023
PaLM: Scaling Language Modeling with Pathways Aakanksha Chowdhery Sharan Narang Jacob Devlin Maarten Bosma Gaurav Mishra ... Kathy Meier-Hellstern Douglas Eck J. Dean Slav Petrov Noah Fiedel PILM LRM 495 6,240 0 05 Apr 2022
LaMDA: Language Models for Dialog Applications R. Thoppilan Daniel De Freitas Jamie Hall Noam M. Shazeer Apoorv Kulshreshtha ... Blaise Aguera-Arcas Claire Cui M. Croak Ed H. Chi Quoc Le ALM 137 1,595 0 20 Jan 2022
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations Jiayao Zhang Hua Wang Weijie J. Su 70 8 0 11 Oct 2021
An Unconstrained Layer-Peeled Perspective on Neural Collapse Wenlong Ji Yiping Lu Yiliang Zhang Zhun Deng Weijie J. Su 176 86 0 06 Oct 2021
On the Validity of Modeling SGD with Stochastic Differential Equations (SDEs) Zhiyuan Li Sadhika Malladi Sanjeev Arora 86 80 0 24 Feb 2021
Neural Collapse with Cross-Entropy Loss Jianfeng Lu Stefan Steinerberger MLT 58 65 0 15 Dec 2020
Neural collapse with unconstrained features D. Mixon Hans Parshall Jianzong Pi 72 120 0 23 Nov 2020
A Survey on Contrastive Self-supervised Learning Ashish Jaiswal Ashwin Ramesh Babu Mohammad Zaki Zadeh Debapriya Banerjee F. Makedon SSL 127 1,394 0 31 Oct 2020
Deep Networks from the Principle of Rate Reduction Kwan Ho Ryan Chan Yaodong Yu Chong You Haozhi Qi John N. Wright Yi-An Ma 72 21 0 27 Oct 2020
Prevalence of Neural Collapse during the terminal phase of deep learning training Vardan Papyan Xuemei Han D. Donoho 202 578 0 18 Aug 2020
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations Alexei Baevski Henry Zhou Abdel-rahman Mohamed Michael Auli SSL 285 5,801 0 20 Jun 2020
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks Like Hui M. Belkin UQCV AAML VLM 48 171 0 12 Jun 2020
Supervised Contrastive Learning Prannay Khosla Piotr Teterwak Chen Wang Aaron Sarna Yonglong Tian Phillip Isola Aaron Maschinot Ce Liu Dilip Krishnan SSL 151 4,547 0 23 Apr 2020
A Survey of Deep Learning for Scientific Discovery M. Raghu Erica Schmidt OOD AI4CE 147 123 0 26 Mar 2020
Circle Loss: A Unified Perspective of Pair Similarity Optimization Yifan Sun Changmao Cheng Yuhan Zhang Chi Zhang Liang Zheng Zhongdao Wang Yichen Wei 87 858 0 25 Feb 2020
Revealing the Structure of Deep Neural Networks via Convex Duality Tolga Ergen Mert Pilanci MLT 48 72 0 22 Feb 2020
Big Transfer (BiT): General Visual Representation Learning Alexander Kolesnikov Lucas Beyer Xiaohua Zhai J. Puigcerver Jessica Yung Sylvain Gelly N. Houlsby MQ 286 1,205 0 24 Dec 2019
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks Kaifeng Lyu Jian Li 87 335 0 13 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 125 494 0 12 Jun 2019
Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey Longlong Jing Yingli Tian SSL 123 1,700 0 16 Feb 2019
Transfusion: Understanding Transfer Learning for Medical Imaging M. Raghu Chiyuan Zhang Jon M. Kleinberg Samy Bengio MedIm 77 985 0 14 Feb 2019
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation Greg Yang 154 287 0 13 Feb 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 232 1,650 0 28 Dec 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 188 773 0 12 Nov 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 221 1,272 0 04 Oct 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 106 201 0 02 Oct 2018
Predicting the Generalization Gap in Deep Networks with Margin Distributions Yiding Jiang Dilip Krishnan H. Mobahi Samy Bengio UQCV 93 199 0 28 Sep 2018
An analytic theory of generalization dynamics and transfer learning in deep linear networks Andrew Kyle Lampinen Surya Ganguli OOD 82 131 0 27 Sep 2018
Taskonomy: Disentangling Task Transfer Learning Amir Zamir Alexander Sax Bokui (William) Shen Leonidas Guibas Jitendra Malik Silvio Savarese 123 1,220 0 23 Apr 2018
Group Normalization Yuxin Wu Kaiming He 231 3,660 0 22 Mar 2018
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning Siyuan Ma Raef Bassily M. Belkin 79 289 0 18 Dec 2017
Size-Independent Sample Complexity of Neural Networks Noah Golowich Alexander Rakhlin Ohad Shamir 154 547 0 18 Dec 2017
How regularization affects the critical points in linear networks Amirhossein Taghvaei Jin-Won Kim P. Mehta 63 13 0 27 Sep 2017
Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes Lei Wu Zhanxing Zhu E. Weinan ODL 64 221 0 30 Jun 2017
Parseval Networks: Improving Robustness to Adversarial Examples Moustapha Cissé Piotr Bojanowski Edouard Grave Yann N. Dauphin Nicolas Usunier AAML 138 808 0 28 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 213 2,894 0 14 Mar 2017
On Loss Functions for Deep Neural Networks in Classification Katarzyna Janocha Wojciech M. Czarnecki UQCV 72 551 0 18 Feb 2017
Large-Margin Softmax Loss for Convolutional Neural Networks Weiyang Liu Yandong Wen Zhiding Yu Meng Yang CVBM 81 1,456 0 07 Dec 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 810 3,287 0 24 Nov 2016
Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond Levent Sagun Léon Bottou Yann LeCun UQCV 91 236 0 22 Nov 2016
Topology and Geometry of Half-Rectified Network Optimization C. Freeman Joan Bruna 212 235 0 04 Nov 2016
Instance Normalization: The Missing Ingredient for Fast Stylization Dmitry Ulyanov Andrea Vedaldi Victor Lempitsky OOD 177 3,708 0 27 Jul 2016
Layer Normalization Jimmy Lei Ba J. Kiros Geoffrey E. Hinton 413 10,494 0 21 Jul 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 340 7,985 0 23 May 2016