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🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Database includes nnap potential and other useful data
GPTFF allowing anyone to directly download and run the AI model in an out-of-the-box manner
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新，English version ongoing
Making large AI models cheaper, faster and more accessible
Get up and running with Llama 3.3, Mistral, Gemma 2, and other large language models.
Efficient Python Tricks and Tools for Data Scientists
A Python library and command line interface for automated free energy calculations
This add-on to pymatgen provides tools for analyzing diffusion in materials.
A collection of resources and papers on Diffusion Models
High-Resolution Image Synthesis with Latent Diffusion Models
Diffusion model papers, survey, and taxonomy
A geometry-complete diffusion generative model (GCDM) for 3D molecule generation and optimization (Nature CommsChem)
Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
A Python implementation of global optimization with gaussian processes.
Stable Diffusion web UI
A machine learning course using Python, Jupyter Notebooks, and OpenML
Powerful, efficient particle trajectory analysis in scientific Python.
A curated list of awesome Deep Learning tutorials, projects and communities.
A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.
Roadmap to becoming an Artificial Intelligence Expert in 2022
Molecular dynamics and Monte Carlo soft matter simulation on GPUs.
machine learning and deep learning tutorials, articles and other resources
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
