Oct 29, 2020 · In this paper, we study this fundamental question. We begin by investigating how varying depth and width affects model hidden representations.
Jan 12, 2021 · This paper studies whether neural networks with different architectures, especially different width and depth, learn similar representations.
May 4, 2021 · Despite having different architectures, wide and deep models without the block structure do exhibit representation similarity with each other, ...
Neural networks with different architectures (width and depth learn similar representations). All reviewers agree that the investigations are thorough and the ...
A key factor in the success of deep neural networks is the ability to scale models to improve performance by varying the architecture depth and width.
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A key factor in the success of deep neural networks is the ability to scale models to improve performance by varying the architecture depth and width.
phrasenmaeher/cka: Implementation of paper "Do Wide and ... - GitHub
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Mar 15, 2022 · Implementation of paper "Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth"
Oct 29, 2020 · This paper investigates how varying depth and width affects model hidden representations, finding a characteristic block structure in the hidden ...
Nov 11, 2020 · This study investigates the impact that increasing the model width and depth has on both internal representations and outputs.
The proposed model combines convolution operation and attention mechanism to form a u-shaped framework, which can capture both local and global information.