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Minggao Feng's Projects

aiida-lsmo icon aiida-lsmo

AiiDA workflows for the LSMO laboratory at EPFL

alignn icon alignn

Atomistic Line Graph Neural Network

atom2vec icon atom2vec

Atom2Vec: a simple way to describe atoms for machine learning

autogluon icon autogluon

AutoGluon: AutoML for Image, Text, and Tabular Data

awesome-crystal-gnns icon awesome-crystal-gnns

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

cp2k icon cp2k

Quantum chemistry and solid state physics software package

deepfm4mof icon deepfm4mof

This package provides implementation of MOF recommendation system.

dit icon dit

Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"

dit-3d icon dit-3d

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

gassm icon gassm

GaSSM: GPU-accelerated Simplified String Method

generative-models icon generative-models

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

graphtr icon graphtr

Graph Neural Network for Tag Ranking in Tag-enhanced Video Recommendation(CIKM20)

i-pi icon i-pi

i-PI: a universal force engine

ipcsp icon ipcsp

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

matdeeplearn icon matdeeplearn

MatDeepLearn, package for graph neural networks in materials chemistry

metisfl icon 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.

mofdb icon mofdb

Chemoinformatics database for Metal Oraganic Frameworks ~5Millions rows. Comprehensive API and database format.

mofid icon mofid

A system for rapid identification and analysis of metal-organic frameworks

moformer icon moformer

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

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