overview of datasets for ML in chemistry

Open Babel is a chemical toolbox designed to speak the many languages of chemical data.

Repository for code associated with the uncertainty quantification carpentry, which is part of the MIDAS Schmidt AI in Science Postdoctoral Research program

Keras layers for end-to-end learning with rdkit and pymatgen

The High Throughput Experimentation Analyzer (HiTEA) modules as described in "Probing the Chemical 'Reactome' with High Throughput Experimentation Data" (King-Smith et al.).

This repository contains the notebooks and related materials for the master class "Uncertainty Quantification".

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

Models and data for predicting stability and redox potential of organic radicals

Official Repository for the Uni-Mol Series Methods

Repository for MolFormer

DBSTEP: DFT-based Steric Parameters - python-based tool to extract molecular shape and steric descriptors from essentially any structure format

AIMNet-NSE model

Utilities for working with datasets of chemical reactions, reaction templates and template extraction.

Analyzing chemical databases and predicting reaction conditions with cheminformatics

Compare the performance of different LLM that can be deployed locally on consumer hardware. Run yourself with Colab WebUI.

Code Repository for Machine Learning with PyTorch and Scikit-Learn

A library for efficient similarity search and clustering of dense vectors.

Reaction fingerprints, atlases and classification. Code complementing our Nature Machine Intelligence publication on "Mapping the space of chemical reactions using attention-based neural networks" …

Python for Chemistry, by BPB Publications

EPFL CH-457 "AI for chemistry"

Chemcrow

ChatGPT Chemistry Assistant

Sample code for "Predicting polymer-solvent miscibility using machine-learned Flory-Huggins interaction parameters