Von Neumann Networks
In the mid-twentieth century, mathematician and polymath John von Neumann created a computational system on an array of cells as a simple model of the human brain, where each cell had one of a finite set of roles or states that he predicted would be modelled by a diffusion process. In this work, we show that such a system, when developed in a modern deep learning setting, enables the construction of an artificial neuron having specialized roles that can be learnt. We refer to this neuron as the Von Neumann neuron, and the resulting neural network from such neurons result in a self-engineered design whose architecture is only dependent on the structure and locations of its inputs and outpu...
| Authors | Shekhar S. Chandra |
|---|---|
| Primary category | cs.AI |
| Published | 7 May 2026 |
| Last updated at source | 6 October 2026 |
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