On the Robustness of Neural Collapse and the Neural Collapse of Robustness
Fuente:
arXiv
Guardado en:
| Autores principales: | Su, Jingtong, Zhang, Ya Shi, Tsilivis, Nikolaos, Kempe, Julia |
|---|---|
| Formato: | Preprint |
| Publicado: |
2023
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
The Price of Implicit Bias in Adversarially Robust Generalization
por: Tsilivis, Nikolaos, et al.
Publicado: (2024)
por: Tsilivis, Nikolaos, et al.
Publicado: (2024)
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
por: Feng, Yunzhen, et al.
Publicado: (2024)
por: Feng, Yunzhen, et al.
Publicado: (2024)
Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks
por: Tsilivis, Nikolaos, et al.
Publicado: (2024)
por: Tsilivis, Nikolaos, et al.
Publicado: (2024)
How Reinforcement Learning After Next-Token Prediction Facilitates Learning
por: Tsilivis, Nikolaos, et al.
Publicado: (2025)
por: Tsilivis, Nikolaos, et al.
Publicado: (2025)
Strong Model Collapse
por: Dohmatob, Elvis, et al.
Publicado: (2024)
por: Dohmatob, Elvis, et al.
Publicado: (2024)
On the Geometry of Regularization in Adversarial Training: High-Dimensional Asymptotics and Generalization Bounds
por: Vilucchio, Matteo, et al.
Publicado: (2024)
por: Vilucchio, Matteo, et al.
Publicado: (2024)
Model Collapse Demystified: The Case of Regression
por: Dohmatob, Elvis, et al.
Publicado: (2024)
por: Dohmatob, Elvis, et al.
Publicado: (2024)
EPA: Neural Collapse Inspired Robust Out-of-Distribution Detector
por: Zhang, Jiawei, et al.
Publicado: (2024)
por: Zhang, Jiawei, et al.
Publicado: (2024)
From Concepts to Components: Concept-Agnostic Attention Module Discovery in Transformers
por: Su, Jingtong, et al.
Publicado: (2025)
por: Su, Jingtong, et al.
Publicado: (2025)
Mission Impossible: A Statistical Perspective on Jailbreaking LLMs
por: Su, Jingtong, et al.
Publicado: (2024)
por: Su, Jingtong, et al.
Publicado: (2024)
Robust Weight Imprinting: Insights from Neural Collapse and Proxy-Based Aggregation
por: Westerhoff, Justus, et al.
Publicado: (2025)
por: Westerhoff, Justus, et al.
Publicado: (2025)
Beyond Model Collapse: Scaling Up with Synthesized Data Requires Verification
por: Feng, Yunzhen, et al.
Publicado: (2024)
por: Feng, Yunzhen, et al.
Publicado: (2024)
Neural Collapse versus Low-rank Bias: Is Deep Neural Collapse Really Optimal?
por: Súkeník, Peter, et al.
Publicado: (2024)
por: Súkeník, Peter, et al.
Publicado: (2024)
Trojan Cleansing with Neural Collapse
por: Gu, Xihe, et al.
Publicado: (2024)
por: Gu, Xihe, et al.
Publicado: (2024)
A Tale of Tails: Model Collapse as a Change of Scaling Laws
por: Dohmatob, Elvis, et al.
Publicado: (2024)
por: Dohmatob, Elvis, et al.
Publicado: (2024)
The Prevalence of Neural Collapse in Neural Multivariate Regression
por: Andriopoulos, George, et al.
Publicado: (2024)
por: Andriopoulos, George, et al.
Publicado: (2024)
Activation Saturation and Floquet Spectrum Collapse in Neural ODEs
por: Matzakos, Nikolaos M.
Publicado: (2026)
por: Matzakos, Nikolaos M.
Publicado: (2026)
Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors
por: Rudner, Tim G. J., et al.
Publicado: (2024)
por: Rudner, Tim G. J., et al.
Publicado: (2024)
Rethinking Continual Learning with Progressive Neural Collapse
por: Wang, Zheng, et al.
Publicado: (2025)
por: Wang, Zheng, et al.
Publicado: (2025)
Optimizer choice matters for the emergence of Neural Collapse
por: Zhao, Jim, et al.
Publicado: (2026)
por: Zhao, Jim, et al.
Publicado: (2026)
Pushing Boundaries: Mixup's Influence on Neural Collapse
por: Fisher, Quinn, et al.
Publicado: (2024)
por: Fisher, Quinn, et al.
Publicado: (2024)
Deep Neural Regression Collapse
por: Rangamani, Akshay, et al.
Publicado: (2026)
por: Rangamani, Akshay, et al.
Publicado: (2026)
Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective
por: Sun, Haixiang, et al.
Publicado: (2024)
por: Sun, Haixiang, et al.
Publicado: (2024)
All-around Neural Collapse for Imbalanced Classification
por: Zhang, Enhao, et al.
Publicado: (2024)
por: Zhang, Enhao, et al.
Publicado: (2024)
The Persistence of Neural Collapse Despite Low-Rank Bias
por: Garrod, Connall, et al.
Publicado: (2024)
por: Garrod, Connall, et al.
Publicado: (2024)
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
por: Munn, Michael, et al.
Publicado: (2024)
por: Munn, Michael, et al.
Publicado: (2024)
Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks
por: Liu, Emily
Publicado: (2024)
por: Liu, Emily
Publicado: (2024)
Beyond Unconstrained Features: Neural Collapse for Shallow Neural Networks with General Data
por: Hong, Wanli, et al.
Publicado: (2024)
por: Hong, Wanli, et al.
Publicado: (2024)
Deconstructing the Goldilocks Zone of Neural Network Initialization
por: Vysogorets, Artem, et al.
Publicado: (2024)
por: Vysogorets, Artem, et al.
Publicado: (2024)
DRoP: Distributionally Robust Data Pruning
por: Vysogorets, Artem, et al.
Publicado: (2024)
por: Vysogorets, Artem, et al.
Publicado: (2024)
Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension
por: Andriopoulos, George, et al.
Publicado: (2025)
por: Andriopoulos, George, et al.
Publicado: (2025)
Explaining Grokking and Information Bottleneck through Neural Collapse Emergence
por: Sakamoto, Keitaro, et al.
Publicado: (2025)
por: Sakamoto, Keitaro, et al.
Publicado: (2025)
Flatness is Necessary, Neural Collapse is Not: Rethinking Generalization via Grokking
por: Han, Ting, et al.
Publicado: (2025)
por: Han, Ting, et al.
Publicado: (2025)
Linguistic Collapse: Neural Collapse in (Large) Language Models
por: Wu, Robert, et al.
Publicado: (2024)
por: Wu, Robert, et al.
Publicado: (2024)
Can We Understand Plasticity Through Neural Collapse?
por: Bonifazi, Guglielmo, et al.
Publicado: (2024)
por: Bonifazi, Guglielmo, et al.
Publicado: (2024)
Overcoming the Incentive Collapse Paradox
por: Yin, Qichuan, et al.
Publicado: (2026)
por: Yin, Qichuan, et al.
Publicado: (2026)
Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse
por: Jacot, Arthur, et al.
Publicado: (2024)
por: Jacot, Arthur, et al.
Publicado: (2024)
Detecting Out-of-Distribution Through the Lens of Neural Collapse
por: Liu, Litian, et al.
Publicado: (2023)
por: Liu, Litian, et al.
Publicado: (2023)
Towards Understanding Neural Collapse: The Effects of Batch Normalization and Weight Decay
por: Pan, Leyan, et al.
Publicado: (2023)
por: Pan, Leyan, et al.
Publicado: (2023)
Neural Collapse in Multi-label Learning with Pick-all-label Loss
por: Li, Pengyu, et al.
Publicado: (2023)
por: Li, Pengyu, et al.
Publicado: (2023)
Ejemplares similares
-
The Price of Implicit Bias in Adversarially Robust Generalization
por: Tsilivis, Nikolaos, et al.
Publicado: (2024) -
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
por: Feng, Yunzhen, et al.
Publicado: (2024) -
Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks
por: Tsilivis, Nikolaos, et al.
Publicado: (2024) -
How Reinforcement Learning After Next-Token Prediction Facilitates Learning
por: Tsilivis, Nikolaos, et al.
Publicado: (2025) -
Strong Model Collapse
por: Dohmatob, Elvis, et al.
Publicado: (2024)