%0 Journal Article %1 cuomo2022scientific %A Cuomo, Salvatore %A Di Cola, Vincenzo Schiano %A Giampaolo, Fabio %A Rozza, Gianluigi %A Raissi, Maizar %A Piccialli, Francesco %D 2022 %J arXiv preprint arXiv:2201.05624 %K pde nn neural network partial differential equation round1 citedby:scholar:count:45 citedby:scholar:timestamp:2022-11-11 %T Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next

@article{cuomo2022scientific, added-at = {2022-11-11T12:35:43.000+0100}, author = {Cuomo, Salvatore and Di Cola, Vincenzo Schiano and Giampaolo, Fabio and Rozza, Gianluigi and Raissi, Maizar and Piccialli, Francesco}, biburl = {https://www.bibsonomy.org/bibtex/2877c2d9426ecb636496eba3e95eb5a3d/becker}, interhash = {0eb41397f160179af656378c1027f9d7}, intrahash = {877c2d9426ecb636496eba3e95eb5a3d}, journal = {arXiv preprint arXiv:2201.05624}, keywords = {pde nn neural network partial differential equation round1 citedby:scholar:count:45 citedby:scholar:timestamp:2022-11-11}, timestamp = {2022-11-11T12:35:43.000+0100}, title = {Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next}, year = 2022 }