Finite operator learning: Bridging neural operators and numerical methods for efficient parametric solution and optimization of pdes
We introduce a method that combines neural operators, physics-informed machine learning,
and standard numerical methods for solving PDEs. The proposed approach extends each of …
and standard numerical methods for solving PDEs. The proposed approach extends each of …
MODNO: Multi Operator Learning With Distributed Neural Operators
Z Zhang - arXiv preprint arXiv:2404.02892, 2024 - arxiv.org
The study of operator learning involves the utilization of neural networks to approximate
operators. Traditionally, the focus has been on single-operator learning (SOL). However …
operators. Traditionally, the focus has been on single-operator learning (SOL). However …