ncfrey / pummlLinks
Positive and Unlabeled Materials Machine Learning (pumml) is a code that uses semi-supervised machine learning to classify materials from only positive and unlabeled examples.
☆37Updated last year
Alternatives and similar repositories for pumml
Users that are interested in pumml are comparing it to the libraries listed below
Sorting:
- R codes for generating candidates of novel polymers with high thermal conductivity using iqspr (R package)☆14Updated 6 years ago
- A knowledge graph for Materials Science.☆75Updated 9 months ago
- Autonomous generator of novel organic compounds from target physicochemical properties. It accelerates innovations in novel materials and…☆16Updated 7 years ago
- Unsupervised fingerprinting of disordered solids leading to analogical materials discovery.☆10Updated 2 years ago
- Autonomous characterization of molecular compounds from small datasets without descriptors☆44Updated last month
- Deep Learning the Chemistry of Materials From Only Elemental Composition for Enhancing Materials Property Prediction☆97Updated 2 years ago
- Crystal Graph Neural Networks☆109Updated last year
- Mirror of http://zeoplusplus.org/☆9Updated 7 years ago
- The inverse materials design is a key topic of materials science nowadays. The proposed software solutions are useful tools for decision …☆11Updated 5 years ago
- image-based generative model for inverse design of solid state materials☆40Updated 3 years ago
- Text mining synthesis information in metal organic framework☆13Updated 3 years ago
- ML4Chem: Machine Learning for Chemistry and Materials☆98Updated 8 months ago
- Graph Learning over Macromolecule Representations