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Perturbation Analysis of Neural Collapse

Perturbation Analysis of Neural Collapse

29 October 2022
Tom Tirer
Haoxiang Huang
Jonathan Niles-Weed
    AAML
ArXivPDFHTML

Papers citing "Perturbation Analysis of Neural Collapse"

24 / 24 papers shown
Title
Robust Weight Imprinting: Insights from Neural Collapse and Proxy-Based Aggregation
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
56
0
0
18 Mar 2025
Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization
Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization
Noam Razin
Sadhika Malladi
Adithya Bhaskar
Danqi Chen
Sanjeev Arora
Boris Hanin
89
12
0
11 Oct 2024
Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural
  Collapse
Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse
Arthur Jacot
Peter Súkeník
Zihan Wang
Marco Mondelli
26
1
0
07 Oct 2024
SGW-based Multi-Task Learning in Vision Tasks
SGW-based Multi-Task Learning in Vision Tasks
Ruiyuan Zhang
Yuyao Chen
Yuchi Huo
Jiaxiang Liu
Dianbing Xi
Jie Liu
Chao Wu
26
0
0
03 Oct 2024
The Prevalence of Neural Collapse in Neural Multivariate Regression
The Prevalence of Neural Collapse in Neural Multivariate Regression
G. Andriopoulos
Zixuan Dong
Li Guo
Zifan Zhao
Keith Ross
30
2
0
06 Sep 2024
Beyond Unconstrained Features: Neural Collapse for Shallow Neural
  Networks with General Data
Beyond Unconstrained Features: Neural Collapse for Shallow Neural Networks with General Data
Wanli Hong
Shuyang Ling
27
3
0
03 Sep 2024
Linguistic Collapse: Neural Collapse in (Large) Language Models
Linguistic Collapse: Neural Collapse in (Large) Language Models
Robert Wu
V. Papyan
33
11
0
28 May 2024
Neural Collapse versus Low-rank Bias: Is Deep Neural Collapse Really
  Optimal?
Neural Collapse versus Low-rank Bias: Is Deep Neural Collapse Really Optimal?
Peter Súkeník
Marco Mondelli
Christoph H. Lampert
AI4CE
32
5
0
23 May 2024
Progressive Feedforward Collapse of ResNet Training
Progressive Feedforward Collapse of ResNet Training
Sicong Wang
Kuo Gai
Shihua Zhang
AI4CE
25
4
0
02 May 2024
Average gradient outer product as a mechanism for deep neural collapse
Average gradient outer product as a mechanism for deep neural collapse
Daniel Beaglehole
Peter Súkeník
Marco Mondelli
Misha Belkin
AI4CE
25
12
0
21 Feb 2024
Cross Entropy versus Label Smoothing: A Neural Collapse Perspective
Cross Entropy versus Label Smoothing: A Neural Collapse Perspective
Li Guo
Keith Ross
Zifan Zhao
G. Andriopoulos
Shuyang Ling
Yufeng Xu
Zixuan Dong
UQCV
NoLa
14
7
0
06 Feb 2024
Neural Collapse for Cross-entropy Class-Imbalanced Learning with
  Unconstrained ReLU Feature Model
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Feature Model
Hien Dang
Tho Tran
Tan Minh Nguyen
Nhat Ho
8
11
0
04 Jan 2024
On the Robustness of Neural Collapse and the Neural Collapse of
  Robustness
On the Robustness of Neural Collapse and the Neural Collapse of Robustness
Jingtong Su
Ya Shi Zhang
Nikolaos Tsilivis
Julia Kempe
AAML
15
4
0
13 Nov 2023
Generalized Neural Collapse for a Large Number of Classes
Generalized Neural Collapse for a Large Number of Classes
Jiachen Jiang
Jinxin Zhou
Peng Wang
Qing Qu
Dustin Mixon
Chong You
Zhihui Zhu
AI4CE
24
20
0
09 Oct 2023
Neural Collapse for Unconstrained Feature Model under Cross-entropy Loss
  with Imbalanced Data
Neural Collapse for Unconstrained Feature Model under Cross-entropy Loss with Imbalanced Data
Wanli Hong
Shuyang Ling
14
12
0
18 Sep 2023
A Neural Collapse Perspective on Feature Evolution in Graph Neural
  Networks
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks
Vignesh Kothapalli
Tom Tirer
Joan Bruna
22
10
0
04 Jul 2023
Quantifying the Variability Collapse of Neural Networks
Quantifying the Variability Collapse of Neural Networks
Jing-Xue Xu
Haoxiong Liu
26
4
0
06 Jun 2023
The Law of Parsimony in Gradient Descent for Learning Deep Linear
  Networks
The Law of Parsimony in Gradient Descent for Learning Deep Linear Networks
Can Yaras
P. Wang
Wei Hu
Zhihui Zhu
Laura Balzano
Qing Qu
20
17
0
01 Jun 2023
Neural (Tangent Kernel) Collapse
Neural (Tangent Kernel) Collapse
Mariia Seleznova
Dana Weitzner
Raja Giryes
Gitta Kutyniok
H. Chou
11
6
0
25 May 2023
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained
  Features Model
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model
Peter Súkeník
Marco Mondelli
Christoph H. Lampert
13
20
0
22 May 2023
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced
  Data
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data
Hien Dang
Tho Tran
T. Nguyen
Hung The Tran
Nhat Ho
Hung Tran
26
27
0
01 Jan 2023
An Unconstrained Layer-Peeled Perspective on Neural Collapse
An Unconstrained Layer-Peeled Perspective on Neural Collapse
Wenlong Ji
Yiping Lu
Yiliang Zhang
Zhun Deng
Weijie J. Su
122
83
0
06 Oct 2021
Continuous vs. Discrete Optimization of Deep Neural Networks
Continuous vs. Discrete Optimization of Deep Neural Networks
Omer Elkabetz
Nadav Cohen
55
44
0
14 Jul 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse
  in Imbalanced Training
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training
Cong Fang
Hangfeng He
Qi Long
Weijie J. Su
FAtt
114
162
0
29 Jan 2021
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