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regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty bounds and deriving
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Gaussian process regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty
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longer-lasting charging strategy for Li-ion cells using two complementary approaches. (1) By testing commercial cells under various controllable stress factors and integrating lifetime prediction models
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: - Distributed task and motion planning - Multi-agent navigation in constrained environments - Predictive collaboration with heterogeneous teaming - Perception-aware predictive motion planning - Distributed and
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-agent navigation in constrained environments - Predictive collaboration with heterogeneous teaming - Perception-aware predictive motion planning - Distributed and cooperative control - Body aware motion
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computational technologies to discover how biomolecules and organisms function and interact. We pioneer new methods for prediction, prevention, diagnostics and treatment of diseases. At the Division of Systems
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will be part of this research ecosystem. Project description A key missing capability in current cancer research is the ability to predict how a particular cancer cell will respond to a perturbation (e.g
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will be part of this research ecosystem. Project description A key missing capability in current cancer research is the ability to predict how a particular cancer cell will respond to a perturbation (e.g
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. We use advanced computational technologies to discover how biomolecules and organisms function and interact. We pioneer new methods for prediction, prevention, diagnostics and treatment of diseases. In
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with: The Halberg Group (University of Copenhagen) – experts in insect physiology and osmoregulatory control The Collin Lab (Lund University) – leaders in bacterial pathogenesis and enzymatic immune