Finite Volume Neural Network: Modeling Subsurface Contaminant Transport. - Timothy Praditia; Matthias Karlbauer; Sebastian Otte; Sergey Oladyshkin; Martin V. Butz; Wolfgang Nowak (CoRR, 2021)

Infering Boundary Conditions in Finite Volume Neural Networks. - Cosku Can Horuz; Matthias Karlbauer; Timothy Praditia; Martin V. Butz; Sergey Oladyshkin; Wolfgang Nowak; Sebastian Otte (ICANN (1), 2022)

Composing Partial Differential Equations with Physics-Aware Neural Networks. - Matthias Karlbauer; Timothy Praditia; Sebastian Otte; Sergey Oladyshkin; Wolfgang Nowak; Martin V. Butz (ICML, 2022)

PDEBench: An Extensive Benchmark for Scientific Machine Learning. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (NeurIPS, 2022)

PDEBench Pretrained Models. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2022)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2022)

Finite Volume Neural Network. - Timothy Praditia; Matthias Karlbauer; Sebastian Otte; Sergey Oladyshkin; Martin V. Butz; Wolfang Nowak (Zenodo, 2022)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2022)

Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network. - Timothy Praditia; Matthias Karlbauer; Sebastian Otte; Sergey Oladyshkin; Martin V. Butz; Wolfgang Nowak (DaRUS, 2022)

Physics-informed neural networks for learning dynamic, distributed and uncertain systems. - Timothy Praditia (2023)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory. - Sergey Oladyshkin; Timothy Praditia; Ilja Kröker; Farid Mohammadi; Wolfgang Nowak; Sebastian Otte (Neural Networks, 2023)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

PDEBench Pretrained Models. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

Physical Domain Reconstruction with Finite Volume Neural Networks. - Cosku Can Horuz; Matthias Karlbauer; Timothy Praditia; Martin V. Butz; Sergey Oladyshkin; Wolfgang Nowak; Sebastian Otte (Appl. Artif. Intell., 2023)

Inferring Underwater Topography with FINN. - Cosku Can Horuz; Matthias Karlbauer; Timothy Praditia; Sergey Oladyshkin; Wolfgang Nowak; Sebastian Otte (CoRR, 2024)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2024)