Web Neural Network with Complete DiGraphs
January 07, 2024 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Frank Li
arXiv ID
2401.04134
Category
cs.NE: Neural & Evolutionary
Cross-listed
cs.AI
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
This paper introduces a new neural network model that aims to mimic the biological brain more closely by structuring the network as a complete directed graph that processes continuous data for each timestep. Current neural networks have structures that vaguely mimic the brain structure, such as neurons, convolutions, and recurrence. The model proposed in this paper adds additional structural properties by introducing cycles into the neuron connections and removing the sequential nature commonly seen in other network layers. Furthermore, the model has continuous input and output, inspired by spiking neural networks, which allows the network to learn a process of classification, rather than simply returning the final result.
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