Stars
An R Framework for Climate Data Access and Post-processing
TESSERA is a foundation model that can process time-series satellite imagery for applications such as land classification and canopy height prediction. Developed at the University of Cambridge, it …
This script creates polygons across a selected network of streets keeping an eye on the intersection and by managing the size and shape of the polygons over the network of streets.
Lime: Explaining the predictions of any machine learning classifier
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Model Context Protocol (MCP) that allows LLMs to use QGIS Desktop
Reference PyTorch implementation and models for DINOv3
Embedding Atlas is a tool that provides interactive visualizations for large embeddings. It allows you to visualize, cross-filter, and search embeddings and metadata.
The Galileo family of pretrained remote sensing models
OpenMMLab Foundational Library for Training Deep Learning Models
Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthr…
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
Provides a SpatialDataGenerator class for accessing spatial data.
SXL: Spatially explicit learning of geographic processes with auxiliary tasks
Case study of different statistical and machine learning models for spatial data
A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting
Scalable and user friendly neural 🧠 forecasting algorithms.
Bayesian Neural Field models for prediction in large-scale spatiotemporal datasets
Supplementary package for "Spatio-Temporal Statistics with R" by C.K. Wikle, A. Zammit-Mangion, and N. Cressie
Python package for the deep distribution regression method.