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
- ☆11Updated last year
- Autonomous generator of novel organic compounds from target physicochemical properties. It accelerates innovations in novel materials and…☆16Updated 7 years ago
- ☆21Updated 6 years ago
- Interactive plots with chemical structures☆15Updated 6 years ago
- Quantum mechanical descriptor generation☆55Updated 5 years ago
- A web based application predicts water solubility of any given chemical compound known or unknown☆13Updated 4 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
- ☆12Updated 7 years ago
- Mol2vec notebooks for use with Binder service☆29Updated 7 years ago
- Autonomous characterization of molecular compounds from small datasets without descriptors☆44Updated 5 months ago
- ☆11Updated 3 years ago
- Unsupervised fingerprinting of disordered solids leading to analogical materials discovery.☆10Updated 2 years ago
- A Graph Neural Network (Geometric machine learning) for molecular generation☆21Updated 6 years ago
- Pipeline for automated extraction of chemical property information from scientific documents☆19Updated 7 years ago
- A knowledge graph for Materials Science.☆75Updated last year
- Python library for optimizing molecular structures and determining chemical reaction pathways.☆17Updated last year
- Graph Learning over Macromolecule Representations☆23Updated 2 years ago
- Variational Autoencoder for Molecules☆32Updated 6 years ago
- AI for a cure, a combination of Latent-GAN and VAE-JTNN to create 100% valid drug like molecules☆10Updated 5 years ago
- Benchmarking human and machine learning performance.☆34Updated 5 years ago
- Mixed DNN Architectures for Predicting Properties using Multiple Molecular Representations☆23Updated 6 years ago
- Experimental design and Bayesian optimization library in Python/PyTorch☆55Updated last year
- Genetic Algorithm Machine Learning (GAML) software package for automated force field parameterization.☆15Updated 4 years ago
- ☆63Updated 3 years ago
- a universal machine learning model for predicting properties of Chemical Compounds☆11Updated 6 years ago
- Deep learning for molecules quantum chemistry properties prediction☆40Updated 4 years ago
- ☆21Updated 2 years ago
- Prediction of pKa from chemical structure using machine learning approaches，molecular similarity and so on☆24Updated last year
- A concise and easy-to-customize reimplementation of "ChemProp" (Yang et al, 2019) in PyTorch Geometric.☆23Updated 3 years ago