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cs.LG2022★ 1 cited
Anisotropic, Sparse and Interpretable Physics-Informed Neural Networks for PDEs
Amuthan A. Ramabathiran, Prabhu Ramachandran
There has been a growing interest in the use of Deep Neural Networks (DNNs) to solve Partial Differential Equations (PDEs). Despite the promise that such approaches hold, there are…
cs.LG2021★ 96 cited
SPINN: Sparse, Physics-based, and partially Interpretable Neural Networks for PDEs
Amuthan A. Ramabathiran, Prabhu Ramachandran
We introduce a class of Sparse, Physics-based, and partially Interpretable Neural Networks (SPINN) for solving ordinary and partial differential equations (PDEs). By reinterpreting…