dhw059

pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

DeepModelFusion

L-G-DCNN improves material property predictions with a fusion strategy based on Chemical Environment Classification Vector.

BatteryManagementSystem

Integrated software for comprehensive BMS strategy validation, SOC accuracy estimation, cell boundary definition, and battery data analysis.

DenseGNN

DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules

maml

maml (MAterials Machine Learning) is a Python package that aims to provide useful high-level interfaces that make ML for materials science as easy as possible.

LLM-predictor

The strategy of material dataset based on Tokens, utilizing LLM to achieve material prediction, discovery, and design.

aiida-core

The official repository for the AiiDA code

AIRS

Artificial Intelligence Research for Science (AIRS)

AlphaCrystal

AlphaCrytal: Contact map based deep learning algorithm for crystal structure prediction

atomate

atomate is a powerful software for computational materials science and contains pre-built workflows.

dhw059/DeepModelFusion

L-G-DCNN improves material property predictions with a fusion strategy based on Chemical Environment Classification Vector.

dhw059/BatteryManagementSystem

Integrated software for comprehensive BMS strategy validation, SOC accuracy estimation, cell boundary definition, and battery data analysis.

dhw059/DenseGNN

DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules

dhw059/deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics

dhw059/DiffCSP

dhw059/DeepLearing-Interview-Awesome-2024

AIGC-interview/CV-interview/LLMs-interview面试问题与答案集合仓，同时包含工作和科研过程中的新想法、新问题、新资源与新项目

dhw059/aiida-core

The official repository for the AiiDA code

dhw059/llama3-from-scratch

llama3 implementation one matrix multiplication at a time

dhw059/matbench

Matbench: Benchmarks for materials science property prediction

dhw059/GGNN4Science

dhw059/daily-interview

Datawhale成员整理的面经，内容包括机器学习，CV，NLP，推荐，开发等，欢迎大家star

dhw059/mendeleev

A python package for accessing various properties of elements, ions and isotopes in the periodic table of elements.

dhw059/materials_discovery

dhw059/QAnything

Question and Answer based on Anything.

dhw059/LLM-predictor

The strategy of material dataset based on Tokens, utilizing LLM to achieve material prediction, discovery, and design.

dhw059/maml

maml (MAterials Machine Learning) is a Python package that aims to provide useful high-level interfaces that make ML for materials science as easy as possible.

dhw059/ChatDev

Create Customized Software using Natural Language Idea (through LLM-powered Multi-Agent Collaboration)

dhw059/fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

dhw059/atomate

atomate is a powerful software for computational materials science and contains pre-built workflows.

dhw059/MolTC

dhw059/Uni-MOF

dhw059/GraphEdit

"GraphEdit: Large Language Models for Graph Structure Learning"

dhw059/rdkit

The official sources for the RDKit library

dhw059/deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

dhw059/awesome-ai-papers

A curated list of the most impressive AI papers

dhw059/modnet

MODNet: a framework for machine learning materials properties

dhw059/gnn

TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.

dhw059/Qwen-Agent

Agent framework and applications built upon Qwen, featuring Plugins, Code Interpreter, RAG, and Chrome extension.

dhw059/Qwen

The official repo of Qwen (通义千问) chat & pretrained large language model proposed by Alibaba Cloud.

dhw059/AIRS

Artificial Intelligence Research for Science (AIRS)