txie-93 / cdvaeLinks
An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
☆351Updated last year
Alternatives and similar repositories for cdvae
Users that are interested in cdvae are comparing it to the libraries listed below
Sorting:
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆292Updated 4 months ago
- [NeurIPS 2023] The implementation for the paper "Crystal Structure Prediction by Joint Equivariant Diffusion"☆141Updated 8 months ago
- Graph deep learning library for materials☆489Updated last week
- Neural Network Force Field based on PyTorch☆284Updated 3 months ago
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆352Updated 2 months ago
- GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆214Updated 2 years ago
- [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations☆314Updated 10 months ago
- Training neural network potentials☆455Updated last week
- MatDeepLearn, package for graph neural networks in materials chemistry☆199Updated 2 years ago
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆307Updated 8 months ago
- [ICLR 2024] The implementation for the paper "Space Group Constrained Crystal Generation"☆57Updated last month
- Matbench: Benchmarks for materials science property prediction☆179Updated last year
- DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Awa…☆346Updated 2 years ago
- This repository contains a collection of resources and papers on GNN Models on Crystal Solid State Materials☆109Updated 2 months ago
- Workflow for creating and analyzing the Open Catalyst Dataset☆122Updated 10 months ago
- SchNet - a deep learning architecture for quantum chemistry☆278Updated 7 years ago
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆203Updated 3 weeks ago
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆208Updated 2 weeks ago
- Official code for Periodic Graph Transformers for Crystal Material Property Prediction (NeurIPS 2022)☆109Updated 2 years ago
- A Large Language Model of the CIF format for Crystal Structure Generation☆143Updated 3 months ago
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆595Updated this week
- FTCP code☆35Updated 2 years ago
- NequIP is a code for building E(3)-equivariant interatomic potentials☆843Updated last week
- A repository for implementing graph network models based on atomic structures.☆100Updated last year
- MACE foundation models (MP, OMAT, Matpes)☆182Updated last month
- Torch-native, batchable, atomistic simulations.☆390Updated this week
- An open-source Python package for creating fast and accurate interatomic potentials.☆340Updated 3 months ago
- AI for crystal materials☆101Updated this week
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆989Updated last week
- An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]☆26Updated last year