Artificial Intelligence Research for Science (AIRS)

2021年最新总结，推荐工程师合适读本，计算机科学，软件技术，创业，思想类，数学类，人物传记书籍

Foundation Model for Materials - FM4M

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.

NequIP is a code for building E(3)-equivariant interatomic potentials

High accuracy RAG for answering questions from scientific documents with citations

Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 2, and other large language models.

Bayesian Optimization and Design of Experiments

Graph deep learning library for materials

Kolmogorov Arnold Networks

Open MatSci ML Toolkit is a framework for prototyping and scaling out deep learning models for materials discovery supporting widely used materials science datasets, and built on top of PyTorch Lig…

The materials for the Spring Mathematics in Materials course at the UTK MSE

Neural force field learning toolkit

Friends don't let friends make certain types of data visualization - What are they and why are they bad.

Fit interpretable models. Explain blackbox machine learning.

The QMOF Database: A database of quantum-mechanical properties for metal-organic frameworks.

Chemist AI Agent for Developing Materials Datasets with Natural Language Prompts

A toolkit for visualizations in materials informatics.

ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text Data

The Wren sits on its Roost in the Aviary.

✨✨Latest Advances on Multimodal Large Language Models

Library for steering campaigns of simulations on supercomputers

Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.

Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.

Fast SHAP value computation for interpreting tree-based models

atomate2 is a library of computational materials science workflows