cs.NE · 2026-07-30 · No. 69
Neural and Evolutionary Computing, 2026-07-30.
2 new papers in cs.NE. Titles, authors,
abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →
01 — The papers
2 entries-
01
The Sparsity Ceiling: Where Spiking Networks Can and Cannot Trade Activity for Energy
Zeyu Wang
cs.NE · cs.LG
Spiking neural networks (SNNs) are promoted as an energy-efficient substrate because sparse, event-driven activity replaces dense multiply-accumulates with cheap accumulates. We argue the energy dividend of sparsity is not a property of SNNs but of the task. Holding architecture fixed and swapping only the hidden unit (continuous vs. leaky-integrate-and-fire), plus a two-sided target-firing-rate probe, we measure how far activity can be...
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02
Shared Symbolic Backbones for Physically Consistent Multi-Output Symbolic Regression
Manuel Rodriguez
cs.NE · cs.AI · cs.CE
Symbolic regression provides analytical expressions, but it is usually applied one output at a time. This is limiting in process systems, where state variables are often coupled through shared physical parameters. Independent symbolic regression can give accurate individual equations that are difficult to interpret as one model. We present a neuro-evolutionary symbolic regression method for coupled multi-output systems. The method searches...
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