oconradh / benchmark_aflowLinks
Benchmark AFLOW Data Sets for Machine Learning doi.org/10.1007/s40192-020-00174-4
☆11Updated 5 years ago
Alternatives and similar repositories for benchmark_aflow
Users that are interested in benchmark_aflow are comparing it to the libraries listed below
Sorting:
- Materials Design by Monte Carlo Tree Search☆35Updated 4 years ago
- ☆34Updated 3 months ago
- ☆14Updated 3 years ago
- Multiobjective active learning with tunable accuracy/efficiency tradeoff and clear stopping criterion.☆41Updated 9 months ago
- Code for performing adversarial attacks on atomistic systems using NN potentials☆40Updated 3 years ago
- Input files for Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., ... & Kozinsky, B. (2021). E(3)-equivarian…☆14Updated 5 months ago
- An elementary MD simulation program written in python☆24Updated 4 years ago
- Unsupervised learning of atomic scale dynamics from molecular dynamics.☆84Updated 4 years ago
- Unsupervised fingerprinting of disordered solids leading to analogical materials discovery.☆10Updated 2 years ago
- Atom2Vec: a simple way to describe atoms for machine learning☆37Updated last year
- Python code for the paper Bayesian Optimization of Nanoporous Materials.☆22Updated 2 years ago
- Supplementary Data for "A graph representation of molecular ensembles for polymer property prediction"☆21Updated 3 years ago
- ☆35Updated 3 years ago
- This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.☆19Updated 3 years ago
- Generative deep learning model for inorganic materials☆19Updated 2 years ago
- ☆16Updated 3 years ago
- Mirror of http://zeoplusplus.org/☆12Updated 7 years ago
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆27Updated 2 years ago
- ☆26Updated 2 years ago
- Accelerated Design of Layered Materials with Bayesian Optimization☆20Updated 7 years ago
- "Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures", Jordan Hoffmann, Louis Maestrati, Yoshihide Sawada, Jian Tang, Je…☆35Updated 6 years ago
- data and code to reduplicate paper: Topological representations of crystalline compounds for the machine-learning prediction of materials…☆22Updated 4 years ago
- ☆58Updated 2 years ago
- These are the slides associated with the GNN tutorial at the APS March Meeting☆21Updated 2 years ago
- Benchmarking☆31Updated 4 years ago
- Quantum mechanical descriptor generation☆55Updated 5 years ago
- ☆15Updated 2 years ago
- image-based generative model for inverse design of solid state materials☆41Updated 3 years ago
- The Block Copolymer Phase Behavior Database (BCDB)☆20Updated last year
- Chemically Directed Atom Swap Hopping -- Crystal structure prediction by swapping atoms in unfavourable chemical environments☆22Updated 2 years ago