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Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks
Physics-informed neural networks (PINNs) have proven an effective tool for solving differential equations, in particular when considering the inverse problem. When inferring solutions and parameters of the differential equation from data, uncertainty estimates are preferable to point estimates, as t
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