Stars
this repo is for exchange with UNIL
a robust MODIS snow cover and phenology product (Google Earth Engine codebase)
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
This repository supplements Aerts et al. 2021 by showing eWaterCycle example notebooks
Python package for running hydrological models