fmggggg

aiida-lsmo

AiiDA workflows for the LSMO laboratory at EPFL

alignn

Atomistic Line Graph Neural Network

Atom2Vec

Atom2Vec: a simple way to describe atoms for machine learning

autogluon

AutoGluon: AutoML for Image, Text, and Tabular Data

AutomatedExperiment_Summer2023

The summer training course on the Bayesian Optimization

Awesome-Crystal-GNNs

This repository contains a collection of resources and papers on GNN Models on Crystal Solid State Materials

awesome-materials-informatics

Curated list of known efforts in materials informatics

CCDCGAN-for-multicomponent-systems

cell2mol

DeepFM4MOF

This package provides implementation of MOF recommendation system.

fmggggg/DeepFM4MOF

This package provides implementation of MOF recommendation system.

fmggggg/alignn

Atomistic Line Graph Neural Network

fmggggg/Atom2Vec

Atom2Vec: a simple way to describe atoms for machine learning

fmggggg/autogluon

AutoGluon: AutoML for Image, Text, and Tabular Data

fmggggg/AutomatedExperiment_Summer2023

The summer training course on the Bayesian Optimization

fmggggg/Awesome-Crystal-GNNs

This repository contains a collection of resources and papers on GNN Models on Crystal Solid State Materials

fmggggg/awesome-materials-informatics

Curated list of known efforts in materials informatics

fmggggg/cell2mol

fmggggg/cp2k

Quantum chemistry and solid state physics software package

fmggggg/CrysTens

fmggggg/DiT

Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"

fmggggg/DiT-3D

🔥🔥🔥Official Codebase of "DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation"

fmggggg/Generative-models

This project aim to share the knowledge and code concerning generative models.

fmggggg/i-pi

i-PI: a universal force engine

fmggggg/ipcsp

Integer Programming encoding for Crystal Structure Prediction with classic and quantum computing bindings

fmggggg/latent-diffusion

High-Resolution Image Synthesis with Latent Diffusion Models

fmggggg/MatDeepLearn

MatDeepLearn, package for graph neural networks in materials chemistry

fmggggg/materials_discovery

fmggggg/MetisFL

MetisFL is a federated learning framework that allows developers to easily federate their machine learning workflows and train their models across distributed data silos without ever collecting the data in a centralized location. The core of the framework is written in C++ and focuses on scalability, speed and resiliency.

fmggggg/mofchecker

Basic sanity checks for MOFs.

fmggggg/mofdscribe

An ecosystem for digital reticular chemistry

fmggggg/MOFormer

Transformer model for structure-agnostic metal-organic frameworks (MOF) property prediction

fmggggg/MOFTransformer

Universal Transfer Learning for MOF

fmggggg/molSimplify

molSimplify code

fmggggg/PORMAKE

Python library for the construction of porous materials using topology and building blocks.

fmggggg/pyrfume

fmggggg/stable-diffusion

A latent text-to-image diffusion model

fmggggg/stk

A Python library which allows construction and manipulation of complex molecules, as well as automatic molecular design and the creation of molecular databases.

fmggggg/StructRepGen

Atomic Structure Generation from Reconstructing Structural Fingerprints

fmggggg/Train_Custom_Dataset

标注自己的数据集，训练、评估、测试、部署自己的人工智能算法