2 citations · 2 across the 1 of their papers we have counts for
2 papers
stat.AP2022★ 2 cited
Process-guidance improves predictive performance of neural networks for carbon turnover in ecosystems
Marieke Wesselkamp, Niklas Moser, Maria Kalweit +2
Despite deep-learning being state-of-the-art for data-driven model predictions, it has not yet found frequent application in ecology. Given the low sample size typical in many envi…
stat.ML2016
Computing AIC for black-box models using Generalised Degrees of Freedom: a comparison with cross-validation
Severin Hauenstein, Carsten F. Dormann, Simon N Wood
Generalised Degrees of Freedom (GDF), as defined by Ye (1998 JASA 93:120-131), represent the sensitivity of model fits to perturbations of the data. As such they can be computed fo…