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It is shown that evaluating just one or two steps of TO is sufficiently informative and that the method scales favorably to thousands of hyperparameters at an expense comparable to only a few standard TO runs, and that the method scales favorably to thousands of hyperparameters at an expense comparable to only a few st...
A Constitutive State Space (CSS) model is introduced that reformulates structured state-space dynamics as an incremental constitutive operator and establishes mechanics-tailored structured state-space dynamics as a computational framework for efficient and discretization-robust data-driven constitutive modeling.
Reinforcement Learning to Choose Optimizers is introduced, which formulates the optimization algorithm choice as a sequential decision-making problem and outperforms every portfolio optimizer at all but the smallest budgets.
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