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Found 4 papers, 1 papers with code
Toward Routing River Water in Land Surface Models with Recurrent Neural Networks
Training of such a model over the continental United States has demonstrated that a single set of model parameters can be used across independent catchments, and that RNNs can outperform physics-based models.
Models for information propagation on graphs
We propose and unify classes of different models for information propagation over graphs.
Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods
The ensemble Kalman methods are shown to behave favourably in the presence of noise in the parameter-to-data map, whereas Langevin methods are adversely affected.
Calibration and Uncertainty Quantification of Convective Parameters in an Idealized GCM
Here we demonstrate an approach to model calibration and uncertainty quantification that requires only $O(10^2)$ model runs and can accommodate internal climate variability.
Gaussian Processes
Statistics Theory
Statistics Theory
