19 citations · 24 across the 3 of their papers we have counts for
3 papers
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…
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…
Does "model-free" forecasting really outperform the "true" model? A reply to Perretti et al
Florian Hartig, Carsten F. Dormann
Estimating population models from uncertain observations is an important problem in ecology. Perretti et al. observed that standard Bayesian state-space solutions to this problem m…