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the department is available at: https://www.umu.se/en/department-of-computing-science/ Project description Graph transformation is a well-established theory that studies computational methods
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including: * Algorithmic game theory * Approximation algorithms * Automata and formal languages * Combinatorics and graph algorithms * Computational complexity * Logic and games * Online and dynamic
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department is available at: https://www.umu.se/en/department-of-computing-science/ Project description Graph transformation is a well-established theory that studies computational methods to transform graphs
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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probability, allow for the application of tools from probability theory to combinatorial problems and motivate the study of the typical properties of various combinatorial models, such as the Erdős–Rényi random
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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Do you like applying mathematical theories in practice to solve real-world challenges? Do you like working with top-notch, internationally recognized industrial partners? Would you like to push the
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and interdisciplinary data integration develop new AI-based methods, tools, scripts, ontologies and a knowledge graph based on RTG research results and relevant literature provide methodological support
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the ANR. PhD student in Graph Signal Processing for the Characterization of Multipolar Electrograms of Persistent Atrial Fibrillation. Responsible for a significant proportion of brain strokes, atrial
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these technologies can only read DNA fragments of limited length. We enable biological interpretation of these sequencing data sets by developing algorithms based on graph theory, discrete optimization and machine