alan-turing-institute/autoemulate

Quantify uncertainty and sensitivities in your computer models with an industry-grade Monte Carlo library.

CrossSim: accuracy simulation of analog in-memory computing

High level API for using machine learning models in OpenMM simulations

Open-source AI agent for scientific research. Analyze data in Python/R with Claude, GPT, Gemini, and more.

:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

A framework for reproducible, comparable benchmarks

Deep-Learning framework for Engineering AI. Built on transformer building blocks, it delivers the full engineering stack, allowing teams to build, train, and operate industrial simulation models across engineering verticals.

Library for efficient training and application of Machine Learning Interatomic Potentials (MLIP)

🎢 Creating and sharing simulation environments for embodied and synthetic data research