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Probabilistic operator learning: generative modeling and uncertainty quantification for foundation models of differential equations
Probabilistic operator learning: generative modeling and uncertainty quantification for foundation models of differential equations arXiv:2509.05186v1 Announce Type: new Abstract: In-context operator networks (ICON) are a class of operator learning methods based on the novel architectures of foundation models. Trained on a diverse set of datasets of initial and boundary conditions paired with corresponding solutions to…