Highlights
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Stars
latent diffusion for forced monthly climate prediction
A tutorial showcasing the process of scaling up a SciML algorithm for multi-node training
Latent Diffusion model for ensemble weather forecasting
A non-exhaustive list of open resources to help environmental scientists get started with machine learning
👋 Xplique is a Neural Networks Explainability Toolbox
CMIP variable to branded variable mapping
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Experiments with pre-processing for computation of weather regimes
Official repository for "Estimating Epistemic and Aleatoric Uncertainty with a Single Model"
A collection of research papers on Diffusion Models for Weather Forecasting.
Tools for converting Unified Forecast System (UFS) output to Analysis Ready, Cloud Optimized (ARCO) format
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
🌦️ A catalogue and categorization of AI-based weather forecasting models.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Delineating Causality in Neural Networks
An index of algorithms for learning causality with data
Python Package for using neural networks to classify hyperspectral data on the moon
netflow.js repository, javascript library for visualizing neural network structure and training on the browser.
Undergraduate work on satellite cloud-inpainting for the Climate Science and ML Grand Challenge @ UMD
High-Performance Symbolic Regression in Python and Julia
Massively parallel training of machine-learning based weather and climate models
This is the repository for Data Readiness Cluster to maintain the AI-ready data checklist.
🎈 Frontend for SondeHub Radiosonde Tracking
Code and documentation for the AMS Short Course: Machine Learning in Python for Environmental Science Problems