On the two-step estimation of the cross-power spectrum for dynamical inverse problems. - Elisabetta Vallarino; Sara Sommariva; Michele Piana; Alberto Sorrentino (CoRR, 2019)

Mathematical modelling of nuclear medicine data. - Michele Piana; Giacomo Caviglia; Sara Sommariva (CoRR, 2020)

The Role of Spectral Complexity in Connectivity Estimation. - Elisabetta Vallarino; Alberto Sorrentino; Michele Piana; Sara Sommariva (Axioms, 2021)

A fast and convergent combined Newton and gradient descent method for computing steady states of chemical reaction networks. - Silvia Berra; Alessandro La Torraca; Federico Benvenuto; Sara Sommariva (CoRR, 2022)

Editorial: Data science in neuro- and onco-biology. - Sara Sommariva; Narayan Puthanmadam Subramaniyam; Michele Piana (Frontiers Appl. Math. Stat., 2023)

Tuning Minimum-Norm regularization parameters for optimal MEG connectivity estimation. - Elisabetta Vallarino; Ana-Sofía Hincapié Casas; Karim Jerbi; Richard M. Leahy; Annalisa Pascarella; Alberto Sorrentino; Sara Sommariva (NeuroImage, 2023)

The impact of ROI extraction method for MEG connectivity estimation: Practical recommendations for the study of resting state data. - Diandra Brkic; Sara Sommariva; Anna-Lisa Schuler; Annalisa Pascarella; Paolo Belardinelli; Silvia L. Isabella; Giovanni Di Pino; Sara Zago; Giulio Ferrazzi; Javier Rasero; Giorgio Arcara; Daniele Marinazzo; et al. (NeuroImage, 2023)

Sparse optimization for estimating the cross-power spectrum in linear inverse models : from theory to the application in brain connectivity. - Laura Carini; Isabella Furci; Sara Sommariva (CoRR, 2024)

Combined Newton-Gradient Method for Constrained Root-Finding in Chemical Reaction Networks. - Silvia Berra; Alessandro La Torraca; Federico Benvenuto; Sara Sommariva (J. Optim. Theory Appl., 2024)

AI-based modular warning machine for risk identification in proximity healthcare. - Chiara Razzetta; Shahryar Noei; Federico Barbarossa; Edoardo Spairani; Monica Roascio; Elisa Barbi; Giulia Ciacci; Sara Sommariva; Sabrina Guastavino; Michele Piana; Matteo Lenge; Gabriele Arnulfo; et al. (CoRR, 2025)