Climate ML should not just predict - it should admit uncertainty. This guide shows how to separate #Epistemic vs #Aleatoric uncertainty, run #MCDropout, add Bayesian layers, and check calibration in #PyTorch for climate projections.

Read the full article: https://codelabsacademy.com/en/blog/uncertainty-quantification-climate-neural-networks-bayesian-layers-mc-dropout?source=mastodon

#ClimateTech #MachineLearning

Climate NN Uncertainty: Bayesian Layers & MC Dropout

Learn epistemic vs aleatoric uncertainty for climate ML. Implement MC dropout and Bayesian layers in PyTorch to calibrate reliable climate projections.