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Prevalence of Neural Collapse during the terminal phase of deep learning training

18 August 2020

Papers citing "Prevalence of Neural Collapse during the terminal phase of deep learning training"

50 / 55 papers shown

Title
Emergence of Hebbian Dynamics in Regularized Non-Local Learners David Koplow Tomaso Poggio Liu Ziyin MLT FedML 63 0 0 23 May 2025
Open-Set Semi-Supervised Learning for Long-Tailed Medical Datasets Daniya Najiha Abdul Kareem Jean Lahoud Mustansar Fiaz Amandeep Kumar Hisham Cholakkal OOD 162 0 0 20 May 2025
The Spotlight Resonance Method: Resolving the Alignment of Embedded Activations George Bird 66 0 0 09 May 2025
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research Patrik Reizinger Randall Balestriero David Klindt Wieland Brendel 178 1 0 17 Apr 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
Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking) Yoonsoo Nam Seok Hyeong Lee Clementine Domine Yea Chan Park Charles London Wonyl Choi Niclas Goring Seungjai Lee AI4CE 188 1 0 28 Feb 2025
Implicit Geometry of Next-token Prediction: From Language Sparsity Patterns to Model Representations Yize Zhao Tina Behnia V. Vakilian Christos Thrampoulidis 178 10 0 20 Feb 2025
A Relative Homology Theory of Representation in Neural Networks Kosio Beshkov 165 0 0 17 Feb 2025
Technical report on label-informed logit redistribution for better domain generalization in low-shot classification with foundation models Behraj Khan T. Syed 481 1 0 29 Jan 2025
Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning Zhongyi Zhou Chaomin Shen Pin Yi Minjie Zhu Yaxin Peng 456 0 0 04 Jan 2025
Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Xinyang Huang Chuang Zhu Ruiying Ren Shengjie Liu Tiejun Huang 183 0 0 03 Jan 2025
Measuring Error Alignment for Decision-Making Systems Binxia Xu Antonis Bikakis Daniel Onah A. Vlachidis Luke Dickens 97 0 0 03 Jan 2025
BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Xiusheng Xu Lei Qi Jingyang Zhou Xin Geng TTA 150 0 0 03 Jan 2025
Dual-Head Knowledge Distillation: Enhancing Logits Utilization with an Auxiliary Head Penghui Yang Chen-Chen Zong Sheng-Jun Huang Lei Feng Bo An 131 1 0 13 Nov 2024
Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the role of model complexity Mouin Ben Ammar David Brellmann Arturo Mendoza Antoine Manzanera Gianni Franchi OODD 104 0 0 04 Nov 2024
Control-oriented Clustering of Visual Latent Representation Han Qi Haocheng Yin Heng Yang SSL 133 2 0 07 Oct 2024
Collapsed Language Models Promote Fairness Jingxuan Xu Wuyang Chen Linyi Li Yao Zhao Yunchao Wei 97 0 0 06 Oct 2024
Formation of Representations in Neural Networks Liu Ziyin Isaac Chuang Tomer Galanti T. Poggio 235 7 0 03 Oct 2024
Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment Naoya Hasegawa Issei Sato 93 0 0 26 Sep 2024
Exploring Information-Theoretic Metrics Associated with Neural Collapse in Supervised Training Kun Song Zhiquan Tan Bochao Zou Jiansheng Chen Huimin Ma Weiran Huang 146 1 0 25 Sep 2024
When resampling/reweighting improves feature learning in imbalanced classification?: A toy-model study Tomoyuki Obuchi Toshiyuki Tanaka 109 0 0 09 Sep 2024
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection Yingwen Wu Ruiji Yu Xinwen Cheng Zhengbao He Xiaolin Huang OODD 102 4 0 28 May 2024
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 78 1 0 13 Sep 2023
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models David X. Wu A. Sahai 72 3 0 23 Jun 2023
The mathematics of adversarial attacks in AI -- Why deep learning is unstable despite the existence of stable neural networks Alexander Bastounis A. Hansen Verner Vlacic AAML OOD 87 28 0 13 Sep 2021
When and How Can Deep Generative Models be Inverted? Aviad Aberdam Dror Simon Michael Elad 83 13 0 28 Jun 2020
Identifying Mislabeled Instances in Classification Datasets Nicolas Müller Karla Markert 47 50 0 11 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 556 42,639 0 03 Dec 2019
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density Behrooz Ghorbani Shankar Krishnan Ying Xiao ODL 89 326 0 29 Jan 2019
Ambitious Data Science Can Be Painless Hatef Monajemi Riccardo Murri Eric Jonas Percy Liang V. Stodden D. Donoho 128 13 0 25 Jan 2019
Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians Vardan Papyan 71 88 0 24 Jan 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 247 1,659 0 28 Dec 2018
The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size Vardan Papyan 75 31 0 16 Nov 2018
Does data interpolation contradict statistical optimality? M. Belkin Alexander Rakhlin Alexandre B. Tsybakov 93 221 0 25 Jun 2018
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate M. Belkin Daniel J. Hsu P. Mitra AI4CE 153 259 0 13 Jun 2018
On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks Jeremias Sulam Aviad Aberdam Amir Beck Michael Elad 100 92 0 02 Jun 2018
Adversarial Noise Attacks of Deep Learning Architectures -- Stability Analysis via Sparse Modeled Signals Yaniv Romano Aviad Aberdam Jeremias Sulam Michael Elad AAML 59 22 0 29 May 2018
Multi-Layer Sparse Coding: The Holistic Way Aviad Aberdam Jeremias Sulam Michael Elad 67 34 0 25 Apr 2018
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning Siyuan Ma Raef Bassily M. Belkin 90 291 0 18 Dec 2017
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 170 924 0 27 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,928 0 25 Aug 2017
Memory-Efficient Implementation of DenseNets Geoff Pleiss Danlu Chen Gao Huang Tongcheng Li Laurens van der Maaten Kilian Q. Weinberger 90 160 0 21 Jul 2017
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks Levent Sagun Utku Evci V. U. Güney Yann N. Dauphin Léon Bottou 56 419 0 14 Jun 2017
Parseval Networks: Improving Robustness to Adversarial Examples Moustapha Cissé Piotr Bojanowski Edouard Grave Yann N. Dauphin Nicolas Usunier AAML 150 808 0 28 Apr 2017
Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond Levent Sagun Léon Bottou Yann LeCun UQCV 95 236 0 22 Nov 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 822 36,892 0 25 Aug 2016
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding Vardan Papyan Yaniv Romano Michael Elad 93 287 0 27 Jul 2016
Discrete Deep Feature Extraction: A Theory and New Architectures Thomas Wiatowski Michael Tschannen Aleksandar Stanić Philipp Grohs Helmut Bölcskei FAtt 62 25 0 26 May 2016
A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction Thomas Wiatowski Helmut Bölcskei FAtt 88 366 0 19 Dec 2015
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,510 0 10 Dec 2015