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Learning dynamical systems using dynamical systems : the reservoir computing approach

Verzelli, Pietro ; Alippi, Cesare (Dir.) ; Livi, Lorenzo (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2022 ; 2022INF001.

Dynamical systems have been used to describe a vast range of phenomena, including physical sciences, biology, neurosciences, and economics just to name a few. The development of a mathematical theory for dynamical systems allowed researchers to create precise models of many phenomena, predicting their behaviors with great accuracy. For many challenges of dynamical systems, highly accurate...

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Graph neural networks : operators and architectures

Grattarola, Daniele ; Alippi, Cesare (Dir.) ; Livi, Lorenzo (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO014.

This thesis explores the field of graph neural networks, a class of deep learning models designed to learn representations of graphs. We organise the work into two parts. In the first part, we focus on the essential building blocks of graph neural networks. We present three novel operators for learning graph representations: one graph convolutional layer and two methods for pooling. We put...

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