bytedance / bambooLinks
BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simulations.
☆145Updated 2 months ago
Alternatives and similar repositories for bamboo
Users that are interested in bamboo are comparing it to the libraries listed below
Sorting:
- SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT, SLICES-PLUS☆138Updated last week
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆59Updated 4 months ago
- Official implementation of DeepDFT model☆87Updated 2 years ago
- A Large Language Model of the CIF format for Crystal Structure Generation☆149Updated 4 months ago
- AI for crystal materials☆109Updated this week
- A Python software package for saddle point optimization and minimization of atomic systems.☆129Updated 2 weeks ago
- ☆117Updated 3 weeks ago
- AI-enhanced computational chemistry☆131Updated last month
- [ICLR 2024] The implementation for the paper "Space Group Constrained Crystal Generation"☆60Updated 2 months ago
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆213Updated last week
- A collection of Neural Network Models for chemistry☆179Updated last month
- Code for automated fitting of machine learned interatomic potentials.☆134Updated 2 weeks ago
- Ionic liquid force field parameters (OPLS-2009IL and OPLS-VSIL)☆73Updated last year
- MACE foundation models (MP, OMAT, Matpes)☆194Updated 2 months ago
- Unsupervised learning of atomic scale dynamics from molecular dynamics.☆85Updated 4 years ago
- A system for rapid identification and analysis of metal-organic frameworks☆69Updated last month
- DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules☆30Updated last year
- DeePMD-kit plugin for various graph neural network models☆52Updated last week
- GRACE models and gracemaker (as implemented in TensorPotential package)☆81Updated last month
- Universal Transfer Learning in Porous Materials, including MOFs.☆115Updated last year
- ☆52Updated 3 years ago
- Crystal Edge Graph Attention Neural Network☆23Updated last year
- Gromacs to Lammps simulation converter☆89Updated 2 years ago
- A unified framework for machine learning collective variables for enhanced sampling simulations☆134Updated last week
- Matbench: Benchmarks for materials science property prediction☆186Updated last year
- Crystal Graph Convolutional Neural Networks tutorial☆31Updated 2 years ago
- Python library for the construction of porous materials using topology and building blocks.☆82Updated 8 months ago
- FTCP code☆36Updated 2 years ago
- A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State Electrolytes☆44Updated 2 months ago
- train and use graph-based ML models of potential energy surfaces☆119Updated last month