NeuronSoup: Evolving Asynchronous, Shared-Neuron Temporal Graphs without Backpropagation
We present NeuronSoup, a neural computation architecture that replaces synchronous layer-by-layer processing with asynchronous, delay-mediated signal propagation through a pool of shared neurons. Each path in the network routes a continuous-valued signal from one input neuron to one output neuron through a variable number of intermediate hidden neurons. Hidden neurons are physically shared across paths: when two paths pass through the same neuron, the second arrival encounters the accumulated state left by the first, producing constructive or destructive interference that depends on signal polarity and arrival timing. The entire architecture -- topology, weights, delays, and connectivity ...
| Authors | Subodh Kalia |
|---|---|
| Primary category | cs.NE |
| Published | 16 July 2026 |
| Last updated at source | 16 July 2026 |
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