Understanding the Initial Condensation of Convolutional Neural Networks

17 May 2023

Papers citing "Understanding the Initial Condensation of Convolutional Neural Networks"

6 / 6 papers shown

Title
An overview of condensation phenomenon in deep learning Zhi-Qin John Xu Yaoyu Zhang Zhangchen Zhou AI4CE 27 0 0 13 Apr 2025
Predicting the Impact of Model Expansion through the Minima Manifold: A Loss Landscape Perspective Pranshu Malviya Jerry Huang Quentin Fournier Sarath Chandar 54 0 0 24 May 2024
Anchor function: a type of benchmark functions for studying language models Zhongwang Zhang Zhiwei Wang Junjie Yao Zhangchen Zhou Xiaolong Li E. Weinan Z. Xu 32 5 0 16 Jan 2024
Unified Batch Normalization: Identifying and Alleviating the Feature Condensation in Batch Normalization and a Unified Framework Shaobo Wang Xiangdong Zhang Dongrui Liu Junchi Yan 13 0 0 27 Nov 2023
Phase Diagram of Initial Condensation for Two-layer Neural Networks Zheng Chen Yuqing Li Tao Luo Zhaoguang Zhou Z. Xu MLT AI4CE 41 8 0 12 Mar 2023
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,634 0 03 Jul 2012