Physics-enhanced deep surrogates for partial differential equations — mentioned by seanhunter

Mon, 05 Feb 2024 14:44:18 GMT

If you look at the paper[1] the authors are 1 from Georgia tech, 1 from IBM "Watson", one from IBM Watson and MIT and 1 from MIT. [1] https://arxiv.org/pdf/2111.05841v3.pdf

Paper and discussion history. A mention is not an endorsement.

Physics-enhanced deep surrogates for partial differential equations — mentioned by djoldman

Mon, 05 Feb 2024 12:44:05 GMT

https://arxiv.org/pdf/2111.05841.pdf > ... Here we present a “physics enhanced deep-surrogate” (“PEDS”) approach towards developing fast surrogate models for complex physical systems, which is described by PDEs. Specifically, a combination of a low fidelity, explainable physics simulator and a neural network generator is proposed, which is trained end-to-end to globally match the output of an expensive high-fidelity numerical solver. Experiments on three exemplar test cases, diffusion, reaction–diffusion, and electromagnetic scattering models, show that a PEDS surrogate can be up to 3× more…

Paper and discussion history. A mention is not an endorsement.

Physics-enhanced deep surrogates for partial differential equations · HackerPapers discussions

Physics-enhanced deep surrogates for partial differential equations — mentioned by seanhunter

Physics-enhanced deep surrogates for partial differential equations — mentioned by djoldman