Python package for hypergraph analysis and visualization.

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

Awesome Few-Shot Class-Incremental Learning

Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"

Collection for Few-shot Learning

LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.

Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.

FSL-Mate: A collection of resources for few-shot learning (FSL).

A curated list of awesome self-supervised methods

Pytorch Geometric Tutorials

Graph Convolutional Networks in PyTorch

🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

A curated list of graph-based fraud, anomaly, and outlier detection papers & resources

Unsupervised time series anomaly detection library

TODS: An Automated Time-series Outlier Detection System

Papers on trustworthy anomaly detection

A curated list of awesome anomaly detection resources

《Pytorch实用教程》（第二版）无论是零基础入门，还是CV、NLP、LLM项目应用，或是进阶工程化部署落地，在这里都有。相信在本书的帮助下，读者将能够轻松掌握 PyTorch 的使用，成为一名优秀的深度学习工程师。

A Python Library for Graph Outlier Detection (Anomaly Detection)

Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications

Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications

Modeling complex networks: An implementation based on Python+NetworkX

复杂网络研究资源整理和基础知识学习

B站GNN教程资料

Repository for benchmarking graph neural networks (JMLR 2023)

Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).

This repository mainly lists some the latest research on graph neural network theory.

A collection of important graph embedding, classification and representation learning papers with implementations.

Anomaly detection related books, papers, videos, and toolboxes