Cascades-Risk Informed Transmission Expansion Planning by Behavioural Cloning. - Anna Varbella; Blazhe Gjorgiev; Giovanni Sansavini; Enrico Zio (ICSRS, 2023)

Geometric deep learning for online prediction of cascading failures in power grids. - Anna Varbella; Blazhe Gjorgiev; Giovanni Sansavini (Reliab. Eng. Syst. Saf., 2023)

PowerGraph: A power grid benchmark dataset for graph neural networks. - Anna Varbella; Kenza Amara; Blazhe Gjorgiev; Mennatallah El-Assady; Giovanni Sansavini (NeurIPS, 2024)

PowerGraph: A power grid benchmark dataset for graph neural networks. - Anna Varbella; Kenza Amara; Blazhe Gjorgiev; Giovanni Sansavini (CoRR, 2024)

A Perspective on Foundation Models for the Electric Power Grid. - Hendrik F. Hamann; Thomas Brunschwiler; Blazhe Gjorgiev; Leonardo S. A. Martins; Alban Puech; Anna Varbella; Jonas Weiss; Juan Bernabé-Moreno; Alexandre Blondin Massé; Seong Choi; Ian T. Foster; Bri-Mathias S. Hodge; et al. (CoRR, 2024)

Physics-Informed GNN for non-linear constrained optimization: PINCO a solver for the AC-optimal power flow. - Anna Varbella; Damien Briens; Blazhe Gjorgiev; Giuseppe Alessio D'Inverno; Giovanni Sansavini (CoRR, 2024)

Goal-oriented graph generation for transmission expansion planning. - Anna Varbella; Blazhe Gjorgiev; Federico Sartore; Enrico Zio; Giovanni Sansavini (Eng. Appl. Artif. Intell., 2025)