Stars
A curated, but incomplete, list of data-centric AI resources.
《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
PKU-DAIR / RAG-Survey
Forked from hymie122/RAG-SurveyCollecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".
A collection of AWESOME things about Graph-Related LLMs.
A collection of AWESOME things about mixture-of-experts
2024中国翻墙软件VPN推荐以及科学上网避坑，稳定好用。对比SSR机场、蓝灯、V2ray、老王VPN、VPS搭建梯子等科学上网与翻墙软件，中国最新科学上网翻墙梯子VPN下载推荐，访问Chatgpt。
A curated list for awesome graph representation learning resources.
Parameterized Explainer for Graph Neural Network
💡 Adversarial attacks on explanations and how to defend them
[ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Your Own View: Graph Contrastive Learning without Prefabricated Dat…
Contrastive Attributed Network Anomaly Detection with Data Augmentation (PAKDD'22)
[TNNLS] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
A collection of papers for graph anomaly detection, and published algorithms and datasets.
Source Code for Paper "DAGAD: Data Augmentation for Graph Anomaly Detection" ICDM 2022
[TKDE 2021] A PyTorch implementation of "Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection".
[CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".
An official source code for paper "Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View", accepted by AAAI 2023.
A curated list of adversarial attacks and defenses papers on graph-structured data.
Adversarial attacks and defenses on Graph Neural Networks.
Awesome literature on imbalanced learning on graphs