Rethinking how to leverage cheap physics for data-efficient neural operators
Read the original at arxiv.org→arXiv:2611.10217v1 Announce Type: new Abstract: Neural operators learn mappings from PDE inputs, such as initial conditions and coefficient fields, to the corresponding solutions. Once trained, they can rapidly...
Original headline: "Rethinking How to Leverage Cheap Physics for Data-Efficient Neural Operators"
Coverage timeline
- Nov 10, 05:00 UTC arXiv cs.LG lead source Rethinking How to Leverage Cheap Physics for Data-Efficient Neural Operators