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testing dynamic equivalencing methods for power system dynamic simulations and integrating these into commercial simulation tools. Dynamic equivalents are simplified representations of complex power system
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the collaboration. In particular, the following open questions will be addressed: What is a sequence-structure-function representation space for molecules in the context of closed-loop optimization, that supports
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transportation decision-making by exploring a wide range of possible scenarios, including unexpected and negative outcomes. By integrating machine learning, metamodeling, and causal representation learning, we aim
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