Principles for initialization and architecture selection in graph neural networks with ReLU activations

DOI10.1137/23m1600621MaRDI QIDQ6664474

Boris Hanin, Gage DeZoort

Publication date: 16 January 2025

Published in: SIAM Journal on Mathematics of Data Science (Search for Journal in Brave)

zbMATH Keywords

initializationoversmoothinggraph neural networks

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Artificial intelligence (68T99)

Cites Work

• Sharp nonasymptotic bounds on the norm of random matrices with independent entries
• Limit of the smallest eigenvalue of a large dimensional sample covariance matrix
• Products of many large random matrices and gradients in deep neural networks
• The Principles of Deep Learning Theory

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