| Conference contribution | Reproducible Statistical Downscaling with the climate4R R-Based Framework: The downscaleR package | 2019 |
| Paper | Statistical Downscaling of Seasonal Wave Forecasts | 2019 |
| Conference contribution | The importance of inductive bias in convolutional models for statistical downscaling | 2019 |
| Paper | Statistical downscaling with package downscaleR: Contribution to the VALUE intercomparison experiment | 2019 |
| Conference contribution | Statistical downscaling with deep learning: A contribution to CORDEX-CORE | 2019 |
| Paper | Validation of spatial variability in downscaling results from the VALUE perfect predictor experiment | 2019 |
| Conference contribution | On the suitability of convolutional neural networks for climate downscaling | 2019 |
| Paper | The VALUE perfect predictor experiment: evaluation of temporal variability | 2019 |
| Paper | Comparison of statistical downscaling methods with respect to extreme events over Europe: Validation results from the perfect predictor experiment of the COST Action VALUE | 2019 |
| Paper | Dynamical and statistical downscaling of seasonal temperature forecasts in Europe: Added value for user applications | 2018 |
