Eigenvalues of neutral networks: Interpolating between hypercubes
The first 16 ‘‘bricklayer’s graphs’’ and the principal eigenvalue of their adjacency matrices.
Discrete Mathematics 339, 1283 (2016)
T. Reeves, R. Farr, J. Blundell, A. Gallagher, T. Fink
A neutral network is a subgraph of a Hamming graph, and its principal eigenvalue determines its robustness: the ability of a population evolving on it to withstand errors. Here we consider the most robust small neutral networks: the graphs that interpolate pointwise between hypercube graphs of consecutive dimension (the point, line, line and point in the square, square, square and point in the cube, and so on). We prove that the principal eigenvalue of the adjacency matrix of these graphs is bounded by the logarithm of the number of vertices, and we conjecture an analogous result for Hamming graphs of alphabet size greater than two.
Network valuation in financial systems
P. Barucca, M. Bardoscia, F. Caccioli, M. D’Errico, G. Visentin, G. Caldarelli, S. Battiston
Mathematical Finance
The space of functions computed by deep layered machines
A. Mozeika, B. Li, D. Saad
Sub. to Physical Review Letters
Replica analysis of overfitting in generalized linear models
T. Coolen, M. Sheikh, A. Mozeika, F. Aguirre-Lopez, F. Antenucci
Sub. to Journal of Physics A
Degree-correlations in a bursting dynamic network model
F. Vanni, P. Barucca
Journal of Economic Interaction and Coordination
Phase transition creates the geometry of the continuum from discrete space
R. Farr, T. Fink
Physical Review E
Intelligently chosen interventions have potential to outperform the diode bridge in power conditioning
F. Liu, Y. Zhang, O. Dahlsten, F. Wang
Scientific Reports
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