bytedance / bambooLinks
BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simulations.
☆126Updated this week
Alternatives and similar repositories for bamboo
Users that are interested in bamboo are comparing it to the libraries listed below
Sorting:
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆56Updated last month
- A collection of Neural Network Models for chemistry☆171Updated last month
- Official implementation of DeepDFT model☆85Updated 2 years ago
- SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT, SLICES-PLUS☆126Updated 3 weeks ago
- AI-enhanced computational chemistry☆115Updated this week
- DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules☆25Updated 10 months ago
- ☆106Updated 3 weeks ago
- A Python software package for saddle point optimization and minimization of atomic systems.☆120Updated last month
- [ICLR 2024] The implementation for the paper "Space Group Constrained Crystal Generation"☆51Updated 5 months ago
- A Large Language Model of the CIF format for Crystal Structure Generation☆134Updated last month
- A unified framework for machine learning collective variables for enhanced sampling simulations☆126Updated 2 weeks ago
- Ionic liquid force field parameters (OPLS-2009IL and OPLS-VSIL)☆70Updated last year
- AI for crystal materials☆91Updated last week
- DeePMD-kit plugin for various graph neural network models☆50Updated this week
- Crystal Edge Graph Attention Neural Network☆23Updated last year
- ☆65Updated 4 years ago
- Code for automated fitting of machine learned interatomic potentials.☆129Updated this week
- MACE foundation models (MP, OMAT, Matpes)☆164Updated this week
- ☆30Updated 2 years ago
- This is a simple but efficient implementation of PaiNN-model for constructing machine learning interatomic potentials☆23Updated 2 years ago
- Universal Transfer Learning in Porous Materials, including MOFs.☆114Updated last year
- A system for rapid identification and analysis of metal-organic frameworks☆62Updated 11 months ago
- train and use graph-based ML models of potential energy surfaces☆112Updated this week
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆200Updated last week
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆79Updated 3 years ago
- A repository for implementing graph network models based on atomic structures.☆95Updated last year
- ☆62Updated 11 months ago
- Unsupervised learning of atomic scale dynamics from molecular dynamics.☆82Updated 3 years ago
- “Ab initio thermodynamics of liquid and solid water” Bingqing Cheng, Edgar A. Engel, JÖrg Behler, Christoph Dellago and Michele Ceriotti…☆29Updated 5 years ago
- Efficient And Fully Differentiable Extended Tight-Binding☆105Updated this week