Author

F. Pijpers

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Preprint Sep 2026

Multiscale Renormalization of Weighted Networks

Recent progress in network renormalization has identified various ways to transform network representations consistently across resolution levels. In particular, the renormalization flow describing how random graph models transform under node aggregation has identified a fixed point corresponding to an aggregation-inva...

Mattia Marzi, F. Pijpers, Diego Garlaschelli · 0 citations

Open access Sep 2026

Uncertainty, probability and causality in hepatology

Bayesian networks are discussed as a framework that unites prognostic modelling with causal decision making, supporting interpretable, adaptive and data-informed care and can move beyond prediction toward decision-relevant understanding.

Benjamin P. M. Laevens, F. Pijpers, Carolin V. Schneider · npj Gut and Liver · 0 citations

Preprint Jun 2026

Analysis of a maximum-entropy based estimator for dynamic random graph models

This framework bridges probabilistic modeling and statistical inference in time-varying networks, providing practical tools for understanding and predicting complex edge dynamics.

Diego Garlaschelli, M. Mandjes, F. Pijpers et al. · 0 citations