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06/19/2023
Super-resolving sparse observations in partial differential equations: A physics-constrained convolutional neural network approach
We propose the physics-constrained convolutional neural network (PC-CNN)...
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06/07/2023
Uncovering solutions from data corrupted by systematic errors: A physics-constrained convolutional neural network approach
Information on natural phenomena and engineering systems is typically co...
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05/24/2023
Short and Straight: Geodesics on Differentiable Manifolds
Manifolds discovered by machine learning models provide a compact repres...
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10/31/2022
Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical Systems
In the absence of high-resolution samples, super-resolution of sparse ob...
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10/28/2022