Neural networks are a priori biased towards Boolean functions with low entropy

25 September 2019

Papers citing "Neural networks are a priori biased towards Boolean functions with low entropy"

8 / 8 papers shown

Title
Neural Redshift: Random Networks are not Random Functions Damien Teney A. Nicolicioiu Valentin Hartmann Ehsan Abbasnejad 103 18 0 04 Mar 2024
Simplicity bias, algorithmic probability, and the random logistic map B. Hamzi K. Dingle 23 3 0 31 Dec 2023
Points of non-linearity of functions generated by random neural networks David Holmes 16 0 0 19 Apr 2023
Do deep neural networks have an inbuilt Occam's razor? Chris Mingard Henry Rees Guillermo Valle Pérez A. Louis UQCV BDL 21 16 0 13 Apr 2023
Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions S. Bhattamishra Arkil Patel Varun Kanade Phil Blunsom 22 44 0 22 Nov 2022
Overview frequency principle/spectral bias in deep learning Z. Xu Yaoyu Zhang Tao Luo FaML 33 66 0 19 Jan 2022
Embedding Principle: a hierarchical structure of loss landscape of deep neural networks Yaoyu Zhang Yuqing Li Zhongwang Zhang Tao Luo Z. Xu 29 21 0 30 Nov 2021
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,746 0 26 Sep 2016