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Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired, method-driven theory to application-driven research. Please find more
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Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired
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techniques more interpretable and biologically meaningful in their application to neural population coding. As a starting point, we will build upon recent advances in graph neural networks (GNNs), particularly
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to neural population coding. As a starting point, we will build upon recent advances in graph neural networks (GNNs), particularly those described by which offer a promising architecture for modelling
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Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired, method-driven theory to application-driven research. Please find more
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are researching this and similar questions. Our goal is to systematically optimise the interaction between people, organisations and technology. With us, your theory also passes the practical test. Bring your