Inducing Neural Collapse to a Fixed Hierarchy-Aware Frame for Reducing Mistake Severity

10 March 2023

Papers citing "Inducing Neural Collapse to a Fixed Hierarchy-Aware Frame for Reducing Mistake Severity"

10 / 10 papers shown

Title
ProHOC: Probabilistic Hierarchical Out-of-Distribution Classification via Multi-Depth Networks Erik Wallin Fredrik Kahl Lars Hammarstrand OODD 52 0 0 27 Mar 2025
Learning and Evaluating Hierarchical Feature Representations Depanshu Sani Saket Anand 45 0 0 10 Mar 2025
Making Better Mistakes in CLIP-Based Zero-Shot Classification with Hierarchy-Aware Language Prompts Tong Liang Jim Davis VLM 96 0 0 04 Mar 2025
Out-of-Distribution Detection with Prototypical Outlier Proxy Mingrong Gong Chaoqi Chen Qingqiang Sun Yue Wang Hui Huang OODD 100 1 0 22 Dec 2024
Linguistic Collapse: Neural Collapse in (Large) Language Models Robert Wu V. Papyan 48 12 0 28 May 2024
It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models Lin Chen Michal Lukasik Wittawat Jitkrittum Chong You Sanjiv Kumar 32 2 0 13 Oct 2023
Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching Ganesh Ramachandra Kini V. Vakilian Tina Behnia Jaidev Gill Christos Thrampoulidis 17 1 0 13 Jun 2023
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model Peter Súkeník Marco Mondelli Christoph H. Lampert 26 21 0 22 May 2023
Understanding Imbalanced Semantic Segmentation Through Neural Collapse Zhisheng Zhong Jiequan Cui Yibo Yang Xiaoyang Wu Xiaojuan Qi Xinming Zhang Jiaya Jia 135 45 0 03 Jan 2023
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training Cong Fang Hangfeng He Qi Long Weijie J. Su FAtt 130 165 0 29 Jan 2021