Simulated data, network reconstruction. Distance between true and inferred networks, in terms of the number of edge differences or ‘Structural Hamming Distance (SHD; smaller values indicate closer approximation to true network) for simulated data at sample sizes of n = 20, 30, 40, 50 per cluster. Results shown for: ℓ₁-penalized network inference applied to complete data, without clustering (‘All Data & L₁’); K-means clustering followed by ℓ₁-penalized network inference applied to the clusters discovered (‘KM & L₁’); clustering using a (full covariance) Gaussian mixture model followed by ℓ₁-penalized network inference [‘GMM (full) & L₁’]; full covariance GMM [‘GMM (full)’]; network clustering using ℓ₁-penalized network inference (‘NC:L₁’); and network clustering using shrinkage-based network inference (‘NC:shrink’). Mean SHD over 100 iterations are shown, and error bars indicate SEM.