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Prolog and Java/JavaScript. Knowledge of Semantic Web technologies (e.g., RDF, OWL, SHACL, SPARQL).Desirable Skills Familiarity with argumentation theory (e.g., ASPIC+, Dung's frameworks). Prior experience
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graph neural networks). Finally, as initiated in [4], a stronger adversary model can also be defined and studied whereby the active adversary who wishes to harm the model is aware of the underlying
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investigate the use of graph neural networks to solve graph and combinatorial problems, such as approximating centrality measures or performing network alignment. • Computational Neuroscience. We are interested
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exploration of the domain, as well as persistence theory. Additionally, we aim to extend the concept of saliency maps [1][2], used in 2D image analysis, to the 3D context. We will investigate the use
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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Approach to Combining Reputation and Contract Theory”. In: IEEE Internet of Things Journal 6.6 (2019), pp. 10700– 10714. [12] Jiawen Kang, Zehui Xiong, Dusit Niyato, Han Yu, Ying-Chang Liang, and Dong In Kim
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, graph theory, satisfiability problems, discrete optimization. Strong interests in chemistry as well as proven competences in programming and ease with formal thinking are a necessity. This PhD project is