Marc Girona-Mata's repositories
lake-snowfall-sensors
Lake as snowfall sensors: automating data post-processing to recover snowfall from lake pressure signal
bad-boids
A deliberately badly programmed implementation of Boids for teaching
baspy
Making it far easier to read in and work with large volumes of climate model output from CMIP5/6
bias_correction
python library for bias correction
cbl-website
CBL website
cl-datasci-pnp
Data Science: Principles and Practice, 2019-20
clim-data
Tools for downloading, parsing and processing climate data from various sources
convcnp
Implementation of the Convolutional Conditional Neural Process
convcnps_hydro
Using Convolutional Conditional Neural Processes (ConvCNPs) for rainfall runoff modelling and hydrological prediction tasks
hydro-logic
Set of tools for hydro analysis
pddp-mountains
probabilistic downscaling of daily precipitation for ungauged mountain locations
gis_metadata_cataloguing
Catalogue and update GIS metadata automatically
GP_algorithm
Implementation of the Grassberger-Procaccia algorithm to estimate the Correlation Dimension of a set of points
hydro-nps
Neural processes for hydrological modelling
lstm_for_pub
Code for our WRR paper "Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning"
MAML-Pytorch
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
mgironamata
A beautiful, simple, clean, and responsive Jekyll theme for academics
neuralhydrology
Python library to train neural networks with a strong focus on hydrological applications.
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
stable-diffusion
A latent text-to-image diffusion model
tilted-non-orthogonal-grid
This repository contains code to create a titled non-orthogonal grid of equally spaced points
WNTR
An EPANET compatible python package to simulate and analyze water distribution networks under disaster scenarios.