# An empirical study of the relation between network architecture and complexity

Source: [An empirical study of the relation between network architecture and complexity](<https://www.sota2.com/research/paper/68fa66ac1e209131cea119aa>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:56:41.004Z

Authors: Emir Konuk, Kevin Smith

Published: 2019-11-11T07:45:01.000Z

## Abstract

In this preregistration submission, we propose an empirical study of how networks handle changes in complexity of the data. We investigate the effect of network capacity on generalization performance in the face of increasing data complexity. For this, we measure the generalization error for an image classification task where the number of classes steadily increases. We compare a number of modern architectures at different scales in this setting. The methodology, setup, and hypotheses described in this proposal were evaluated by peer review before experiments were conducted.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1911.04120>)

[PDF](<https://arxiv.org/pdf/1911.04120.pdf>)