Table 1.

Cross-validation can recover near-optimal sparsity parameters. Without sparsity, MPF consistently overfits to observed data. Reconstruction with 20 nodes (210 parameters), and 128 data points (i.e., the undersampled regime). The more computationally expensive ${\mathcal{N}}_2$ strategy does not improve significantly over the simpler ${\mathcal{N}}_1$.

$\mathit{\beta }$ Range	Optimal KL	KL with CV	Standard MPF
	$n$ = 20, 128 Points
0.01–0.125 (dispersed)	0.22	0.23	1.2
0.125–0.25 (ordered)	0.55	0.56	2.3
0.25–0.5 (near critical)	0.62	0.63	19.4
0.5–1.0 (critical)	0.50	0.54	9.5