| How can we quantify, explain, and apply the uncertainty of complex soil maps predicted with neural networks? K Rau, K Eggensperger, F Schneider, P Hennig, T Scholten Science of The Total Environment, 173720, 2024 | 4 | 2024 |
| How can we quantify, explain and apply the uncertainty of complex soil maps predicted with neural networks? P Hennig, K Rau, T Gläßle, T Scholten EGU General Assembly 2023, 2023 | | 2023 |
| Hierarchical Soil Classification using Gaussian Processes T Gläßle, K Rau, T Scholten, P Hennig EGU General Assembly Conference Abstracts, EGU22-5164, 2022 | | 2022 |
| Spatial prediction of soil type maps with Neural Networks including quantification of model uncertainty K Rau, T Gläßle, P Hennig, T Scholten EGU General Assembly Conference Abstracts, EGU22-2766, 2022 | | 2022 |
| Spatial prediction of soil thickness with Gaussian Process Regression using pedological knowledge described by partial differential equations K Rau, T Gläßle, T Rentschler, P Hennig, T Scholten EGU General Assembly Conference Abstracts, EGU21-3368, 2021 | | 2021 |
| Topographic Kernels for Gaussian Process Regression in Digital Soil Mapping T Gläßle, K Rau, K Schmidt, T Scholten, P Hennig EGU General Assembly Conference Abstracts, EGU21-2452, 2021 | | 2021 |
