Stars
A comprehesive survey about foundation models for weather and cliamte data understanding.
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
A playbook for systematically maximizing the performance of deep learning models.
Graph-based weather forecasting models. Originally, PyTorch implementation of Ryan Keisler's 2022 "Forecasting Global Weather with Graph Neural Networks" paper (https://arxiv.org/abs/2202.07575)
Initial public release of code, data, and model weights for FourCastNet
Neural network loss functions for regression and classification tasks that can say "I don't know".
Deep Learning for Post-Processing Ensemble Weather Forecasts
A plugin for climetlab to retrieve the Eumetnet postprocessing benchmark dataset.
A registry of publicly available datasets on AWS
PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend
A great intro dataset for data exploration & visualization (alternative to iris).
Materials for a workshop on writing reproducible research papers with R Markdown
A game theoretic approach to explain the output of any machine learning model.
Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
Python code for MWR paper 'Using Artificial Neural Networks for Generating Probabilistic Subseasonal Precipitation Forecasts over California'
The papers or tutorials and relative source code of artificial intelligence for meteorology, ocean and environment science.
Bayesian Data Analysis course at Aalto
Updated files to reproduce the analyses from Bracher/Held: Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction
An extension of XGBoost to probabilistic modelling
Isotonic Distributional Regression (IDR)
Probabilistic time series modeling in Python
Use RMarkdown to generate PDF Conference Posters via HTML