| A fully Lagrangian computational model for the integration of mixing and biochemical reactions in anaerobic digestion M Rezavand, D Winkler, J Sappl, L Seiler, M Meister, W Rauch Computers & Fluids 181, 224-235, 2019 | 38 | 2019 |
| Deep learning of preconditioners for conjugate gradient solvers in urban water related problems J Sappl, L Seiler, M Harders, W Rauch arXiv preprint arXiv:1906.06925, 2019 | 13 | 2019 |
| Accelerating surface tension calculation in SPH via particle classification and Monte Carlo integration F Zorilla, M Ritter, J Sappl, W Rauch, M Harders Computers 9 (2), 23, 2020 | 11 | 2020 |
| Machine learning for quantile regression of biogas production rates in anaerobic digesters J Sappl, M Harders, W Rauch Science of the Total Environment 872, 161923, 2023 | 8 | 2023 |
| On the effect of the inlet configuration for anaerobic digester mixing S Dabiri, J Sappl, P Kumar, M Meister, W Rauch Bioprocess and Biosystems Engineering 44 (12), 2455-2468, 2021 | 4 | 2021 |
| Maschinelles Lernen in der Siedlungswasserwirtschaft J Sappl, M Harders, W Rauch Österreichische Wasser-und Abfallwirtschaft 7 (71), 359-368, 2019 | 2 | 2019 |
| Method for generating a compact representation of radar data, radar device and radar data processing circuit P Meissner, M Haltmeier, FB Khalid, A Roger, J Sappl US Patent 11,360,205, 2022 | 1 | 2022 |
| Vorhersage von Zeitserien der Biogasproduktion in anaeroben Faultürmen mit einem Temporal Fusion Transformer J Sappl, M Harders, W Rauch Österreichische Wasser-und Abfallwirtschaft 73 (7), 329-336, 2021 | | 2021 |
| Predicting biogas production rates in anaerobic digesters with a temporal fusion transformer J Sappl, M Harders, W Rauch | | 2021 |
| Machine Learning in Urban Water Management J Sappl, M Harders, W Rauch Österreichische Wasser-und Abfallwirtschaft 71, 359-368, 2019 | | 2019 |
| Low-rank approximation for FMCW automotive radar J Sappl, P Meissner, M Haltmeier 2017 International Conference on Sampling Theory and Applications (SampTA …, 2017 | | 2017 |
| Deep Learning of Preconditioners for Acceleration of Secondary Settling Tank Simulations J Sappl, S Dabiri, M Harders, W Rauch Available at SSRN 4196783, 0 | | |
| Deep Learning of Preconditioners for Conjugate Gradient Solvers in Urban Water Related Problems 2 Deep Learning of Preconditioners 3 J Sappl, L Seiler, M Harders, W Rauch | | |
