3 papers
cond-mat.dis-nn2026
Learning Nonlinear Heterogeneity in Physical Kolmogorov-Arnold Networks
Fabiana Taglietti, Andrea Pulici, Maxwell Roxburgh +10
Physical neural networks typically train linear synaptic weights while treating device nonlinearities as fixed. We show the opposite - by training the synaptic nonlinearity itself,…
math.CA2025
The adaptation property in non-equilibrium chemical systems
E. Franco, J. J. L. Velázquez
The goal of this paper is to understand if the property of adaptation, which is a typical property of many biochemical systems, can be achieved only by biological systems that acti…
math.CA2025
The detailed balance property and chemical systems out of equilibrium
E. Franco, J. J. L. Velázquez
The detailed balance property is a fundamental property that must be satisfied in all the macroscopic systems with a well defined temperature at each point. On the other hand, many…