Popular GitHub Repositories for Scientific Discovery

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

PDF scientific paper translation with preserved formats - 基于 AI 完整保留排版的 PDF 文档全文双语翻译，支持 Google/DeepL/Ollama/OpenAI 等服务，提供 CLI/GUI/Docker/Zotero

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

High accuracy RAG for answering questions from scientific documents with citations

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

mlpack: a fast, header-only C++ machine learning library

Official PyTorch implementation of PTS/PSRN: Fast and efficient symbolic expression discovery through parallelized tree search. Evaluates millions of expressions simultaneously on GPU with automated subtree reuse.

A machine learning software for extracting information from scholarly documents

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

A curated list of resources for using LLMs to develop more competitive grant applications.

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

A library for scientific machine learning and physics-informed learning

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

Data & AI Notebook templates catalog organized by tools, following the IMO (input, model, output) framework for easy usage and discovery..

文本挖掘和预处理工具（文本清洗、新词发现、情感分析、实体识别链接、关键词抽取、知识抽取、句法分析等），无监督或弱监督方法

Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

Zero shot vulnerability discovery using LLMs

Message Passing Neural Networks for Molecule Property Prediction

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)