%0 Journal Article %1 raissi2019physics %A Raissi, Maziar %A Perdikaris, Paris %A Karniadakis, George E %D 2019 %I Elsevier %J Journal of Computational physics %K pde nn neural network partial differential equation round1 citedby:scholar:count:3855 citedby:scholar:timestamp:2022-11-11 %P 686--707 %T Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations %V 378

@article{raissi2019physics, added-at = {2022-11-11T12:37:50.000+0100}, author = {Raissi, Maziar and Perdikaris, Paris and Karniadakis, George E}, biburl = {https://www.bibsonomy.org/bibtex/2c4b64351712214d87ade44f3a4565814/becker}, interhash = {53d1ea8b2196ff86c3d86546b683deec}, intrahash = {c4b64351712214d87ade44f3a4565814}, journal = {Journal of Computational physics}, keywords = {pde nn neural network partial differential equation round1 citedby:scholar:count:3855 citedby:scholar:timestamp:2022-11-11}, pages = {686--707}, publisher = {Elsevier}, timestamp = {2022-11-11T12:37:50.000+0100}, title = {Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations}, volume = 378, year = 2019 }