mlsanityData to 14 Oct 2026

Highly connected dynamic artificial neural networks

arXiv 2302.08928 ↗First posted 17 Feb 2023cs.LGcited by 1

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Abstract (arXiv)

An object-oriented approach to implementing artificial neural networks is introduced in this article. The networks obtained in this way are highly connected in that they admit edges between nodes in any layers of the network, and dynamic, in that the insertion, or deletion, of nodes, edges or layers of nodes can be effected in a straightforward way. In addition, the activation functions of nodes need not be uniform within layers, and can also be changed within individual nodes. Methods for implementing the feedforward step and the backpropagation technique in such networks are presented here. Methods for creating networks, for implementing the various dynamic properties and for saving and recreating networks are also described.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 0 of its 1 references that are in the map. First posted on arXiv 17 Feb 2023.

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