deepstruct – linking deep learning and graph theory-Reference-Cited by-同舟云学术

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deepstruct – linking deep learning and graph theory

Published:2022-02 Issue: Volume:11 Page:100193
ISSN:2665-9638
Container-title:Software Impacts
language:en
Short-container-title:Software Impacts

Author:

Stier Julian^ORCID,Granitzer Michael^ORCID

Publisher

Elsevier BV

Reference9 articles.

1. Pytorch: An imperative style, high-performance deep learning library;Paszke,2019

2. Exploring network structure, dynamics, and function using networkx;Hagberg,2008

3. The lottery ticket hypothesis: Finding sparse, trainable neural networks;Frankle,2018

4. Collective dynamics of ‘small-world’networks;Watts;Nature,1998

5. Experiments on properties of hidden structures of sparse neural networks;Stier,2021

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. 4Ward: A relayering strategy for efficient training of arbitrarily complex directed acyclic graphs;Neurocomputing;2024-02

2. TensorFlow based deep learning layer for Local Derivative Patterns;Software Impacts;2022-12

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