Official implementation of Operator-ProbConserv: OOD UQ for Neural Operators
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Updated
Jul 25, 2024 - Python
Official implementation of Operator-ProbConserv: OOD UQ for Neural Operators
[ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values
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Learning function operators with neural networks.
Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs
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Learning in infinite dimension with neural operators.
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