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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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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In: The International Journal of Advanced Manufacturing Technology, 2015, vol. 81, no. 5-8, p. 1117-1125
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In: Toxicological Sciences, 2017, vol. 160, no. 2, p. 361-370
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In: Tribology Letters, 2015, vol. 57, no. 3, p. 1-10
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Thèse de doctorat : Université de Fribourg, 2020.
The vision of Machine Reading is to automatically understand written text and transform the contained information into machine-readable representations. This thesis approaches this challenge in particular in the context of commercial organizations. Here, an abundance of domain-specific knowledge is frequently stored in unstructured text resources. Existing methods often fail in this scenario,...
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In: The International Journal of Advanced Manufacturing Technology, 2014, vol. 70, no. 5-8, p. 853-867
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In: Holzforschung, 2015, vol. 69, no. 7, p. 839-849
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In: Holzforschung, 2015, vol. 69, no. 7, p. 825-837
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In: Materials and Structures, 2014, vol. 47, no. 8, p. 1409-1424
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