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Open-source code for ''Graph Neural Networks with Adaptive Frequency Response Filter''.
Code for "Adaptive Subgraph Neural Network with Reinforced Critical Structure Mining"
Attribute-guided Sampling for Graph Neural Network, Large Scale algorithm for Heterophilic Graphs
Tensorflow implementation of OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations
Anomaly detection related books, papers, videos, and toolboxes
A curated list of awesome adversarial machine learning resources
Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors
A curated list of data mining papers about fraud detection.
Bringing Old Photo Back to Life (CVPR 2020 oral)
Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.
Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
Source code of "Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation""
🥤 COLA: Clean Object-oriented & Layered Architecture
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning (CoLA), TNNLS-21
Contrastive Attributed Network Anomaly Detection with Data Augmentation (PAKDD'22)
High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model
Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection
Yet another (very simple) approach for adversarial training.
A Deep Graph-based Toolbox for Fraud Detection
Linxiao Yang, Ngai-Man Cheung, Jiaying Li, and Jun Fang, "Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embedding", In ICCV 2019.
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees
Official Code for DragGAN (SIGGRAPH 2023)
Code for DRL-DBSCAN
The implementation for DropMessage.
Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.