Stars
An awesome collection of causality-inspired graph neural networks.
Causal Discovery in Python. Learning causality from data.
A package for running MR In batches and in parallel quickly
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
A resource for learning about Machine learning & Deep Learning
PyTorch tutorials, examples and some books I found 【不定期更新】整理的PyTorch 最新版教程、例子和书籍
List of papers about Proteins Design using Deep Learning
为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…
✨ Light and Fast AI Assistant. Support: Web | iOS | MacOS | Android | Linux | Windows
为机器学习的入门者提供多种基于实例的sklearn、TensorFlow以及自编函数(AnFany)的ML算法程序。
An VGAE implementation using pytorch geometric.
This repository implements variational graph auto encoder by Thomas Kipf.
A VGAE-based model to infer transcription factor regulatory network
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.
Molecular QTL analysis protocol developed by ADSP Functional Genomics Consortium
Separating the direct effects of risk factors for atherosclerotic cardiovascular disease from those mediated by type 2 diabetes
Using SHAP values as feature selection mechanism
A game theoretic approach to explain the output of any machine learning model.
Detecting genome structural variants with deep learning in single molecule sequencing
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)