283 citations · 1.2k across the 17 of their papers we have counts for
Showing physics.comp-phShow all
2 papers · 1 filter
physics.comp-ph2022★ 2 cited
Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of nanoscale heat transport
Lu Lu, Raphael Pestourie, Steven G. Johnson +1
Deep neural operators can learn operators mapping between infinite-dimensional function spaces via deep neural networks and have become an emerging paradigm of scientific machine l…
physics.comp-ph2021★ 49 cited
Physics-informed neural networks with hard constraints for inverse design
Lu Lu, Raphael Pestourie, Wenjie Yao +3
Inverse design arises in a variety of areas in engineering such as acoustic, mechanics, thermal/electronic transport, electromagnetism, and optics. Topology optimization is a major…