RyotaroOKabe / phonon_predictionLinks
We present the virtual node graph neural network (VGNN) to address the challenges in phonon prediction.
☆23Updated last year
Alternatives and similar repositories for phonon_prediction
Users that are interested in phonon_prediction are comparing it to the libraries listed below
Sorting:
- ☆24Updated last year
- GRACE models and gracemaker (as implemented in TensorPotential package)☆80Updated 3 weeks ago
- Code repository for a tutorial based on the "Direct prediction of phonon density of states with Euclidean neural networks"☆31Updated 2 years ago
- Advanced ASE Transition State Tools for ABACUS and Deep-Potential☆39Updated 2 weeks ago
- DistMLIP: A Distributed Inference Library for Fast, Large Scale Atomistic Simulation☆91Updated 3 months ago
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆55Updated 2 months ago
- Crystal Edge Graph Attention Neural Network☆24Updated last year
- Python package to interact with high-dimensional representations of the chemical elements☆46Updated 2 weeks ago
- scripts to load all data from ICSD, Materials Project, and OQMD☆68Updated 3 years ago
- Universal Ensemble-Embedding Graph Neural Network for Direct Prediction of Optical Spectra from Crystal Structures☆32Updated last year
- ☆26Updated last year
- ☆13Updated last year
- A flexible workflow for on-the-fly learning of interatomic potential models.☆31Updated this week
- Wyckoff Inorganic Crystal Generator Framework☆26Updated 10 months ago
- Clean, Uniform and Refined with Automatic Tracking from Experimental Database (CURATED) COFs☆44Updated 2 years ago
- Structural constraint integration in a generative model for the discovery of quantum materials☆25Updated 3 months ago
- OVITO Python modifier to compute the Warren-Cowley parameters.☆37Updated 9 months ago
- Metadynamics code on the G-space.☆14Updated 3 years ago
- Machine-Learning-Based Interatomic Potentials for Catalysis: an Universal Catalytic Large Atomic Model☆50Updated 2 months ago
- Original implementation of CSPML☆29Updated last year
- Active Learning for Machine Learning Potentials☆63Updated last month
- Phonons from ML force fields☆23Updated 6 months ago
- This is the source code for paper "Neural Network Potentials for Accelerated Metadynamics of Oxygen Reduction Kinetics at Au-Water Interf…☆23Updated last year
- ☆113Updated last week
- Online resource for a practical course in machine learning for materials research at Imperial College London (MATE70026)☆101Updated this week
- ASE interface for fully constant potential with VASP☆42Updated last year
- Fine-tuning and distillation workflow for pretrained atomic potentials☆30Updated last week
- Python library for the construction of porous materials using topology and building blocks.☆80Updated 7 months ago
- Generative materials benchmarking metrics, inspired by guacamol and CDVAE.☆41Updated last year
- FTCP code☆36Updated 2 years ago