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Schema for the Open Reaction Database
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
Python library for the construction of porous materials using topology and building blocks.
collection of cage structures extracted from the CSD and analyzed
Universal Transfer Learning in Porous Materials, including MOFs.
A python package to analyze Molecular Dynamics (MD) trajectories of amorphous Metal-Organic Frameworks (MOFs).
A julia package for the manipulation of crystal net representations and topology
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
The QMOF Database: A database of quantum-mechanical properties for metal-organic frameworks.
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.