Probabilistic load forecasting with Reservoir Computing

no code implementations • 24 Aug 2023 • Michele Guerra, Simone Scardapane, Filippo Maria Bianchi

For this reason, point forecasts are not enough hence it is necessary to adopt methods that provide an uncertainty quantification.

Computational Efficiency Load Forecasting +4

Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability

no code implementations • 14 Apr 2023 • Indro Spinelli, Michele Guerra, Filippo Maria Bianchi, Simone Scardapane

Subgraph-enhanced graph neural networks (SGNN) can increase the expressive power of the standard message-passing framework.

Explainability in subgraphs-enhanced Graph Neural Networks

1 code implementation • 16 Sep 2022 • Michele Guerra, Indro Spinelli, Simone Scardapane, Filippo Maria Bianchi

Recently, subgraphs-enhanced Graph Neural Networks (SGNNs) have been introduced to enhance the expressive power of Graph Neural Networks (GNNs), which was proved to be not higher than the 1-dimensional Weisfeiler-Leman isomorphism test.

Graph Classification