%0 Journal Article %1 mandl2025separable %A Mandl, Luis %A Goswami, Somdatta %A Lambers, Lena %A Ricken, Tim %D 2025 %I Elsevier %J Computer methods in applied mechanics and engineering %K %P 117586 %R 10.1016/j.cma.2024.117586 %T Separable physics-informed DeepONet : Breaking the curse of dimensionality in physics-informed machine learning %V 434

@article{mandl2025separable, added-at = {2025-04-15T10:31:14.000+0200}, author = {Mandl, Luis and Goswami, Somdatta and Lambers, Lena and Ricken, Tim}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/26423b0eb64be1cfef02f10cb02aaeef5/unibiblio}, doi = {10.1016/j.cma.2024.117586}, interhash = {e82eaa766ea71e21dcd0d93df23206a0}, intrahash = {6423b0eb64be1cfef02f10cb02aaeef5}, issn = {0045-7825}, journal = {Computer methods in applied mechanics and engineering}, keywords = {}, language = {eng}, pages = 117586, preprinturl = {https://arxiv.org/abs/2407.15887}, publisher = {Elsevier}, timestamp = {2025-04-15T08:31:14.000+0200}, title = {Separable physics-informed DeepONet : Breaking the curse of dimensionality in physics-informed machine learning}, volume = 434, year = 2025 }