thk9178

AutoGPT

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

awesome-chatgpt-prompts

This repo includes ChatGPT prompt curation to use ChatGPT better.

GNNPapers

Must-read papers on graph neural networks (GNN)

deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

chemprop

Message Passing Neural Networks for Molecule Property Prediction

pyscf

Python module for quantum chemistry

papers-for-molecular-design-using-DL

List of Molecular and Material design using Generative AI and Deep Learning

cgcnn

Crystal graph convolutional neural networks for predicting material properties.

GENTRL

Generative Tensorial Reinforcement Learning (GENTRL) model

hgraph2graph

Hierarchical Generation of Molecular Graphs using Structural Motifs

mordred

a molecular descriptor calculator

molecule-generation

Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation

Getting-Started-with-Google-BERT

Getting Started with Google BERT, published by Packt

molSimplify

molSimplify code

MolScribe

Robust Molecular Structure Recognition with Image-to-Graph Generation

RadonPy

RadonPy is a Python library to automate physical property calculations for polymer informatics.

mso

Implementation of the method proposed in the paper "Efficient Multi-Objective Molecular Optimization in a Continuous Latent Space" by Robin Winter, Floriane Montanari, Andreas Steffen, Hans Briem, Frank Noé and Djork-Arné Clevert

deep-learning-with-python-2nd

<케라스 창시자에게 배우는 딥러닝 2판> 도서의 코드 저장소

HierDiff

Implementation of ICML2023 paper : Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D

GGM

graph generative model for molecule

polygnn

polyGNN is a Python library to automate ML model training for polymer informatics.

SGGRL

The implementation of the paper "Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry".

UnifiedMolPretrain

Unified 2D and 3D Pre-Training of Molecular Representations

git-for-everyone

conformer-optimization

Code for finding the ground state conformer

materials

A scraper for the NIST Ionic Liquids Database.

GCNN_PI_glass_transition

naphtha-mixtures

Machine learning method for predicting physicochemical properties of light oil fraction

VAE_MLP_PSO

Code for Data-Driven Multi-Objective Molecular Design of Ionic Liquid with High Generation Efficiency on Small Dataset

Generative-Molecules