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flare

An analytical framework for network traffic and behavioral analytics

flow-feature

extract flow feature from pcap

fooling-lime-shap

Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)

fsl-mate

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

gad-v2

Second version of the gad project

gains

GAINS: Getting stArted wIth biNary analysiS

gan-based-attack

gatv3-sbm-training

Training code for GATv3 SBM

gdn

Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series"

gee

Pytorch implementation of GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection

glocalkd

gnn-embedding-leaks

gnn-in-lanl

Graph Neural Network implemented in the LANL dataset

gnnapp-papers

gnns-easy-to-use

An PyTorch implementation of graph neural networks (GCN, GraphSAGE and GAT) that can be simply imported and used.

goblin

一款适用于红蓝对抗中的仿真钓鱼系统

graph-adversarial-learning

A curated collection of adversarial attack and defense on graph data.

graph-adversarial-learning-literature

A curated list of adversarial attacks and defenses papers on graph-structured data.

graph-anomaly-loss

TNNLS: A Synergistic Approach for Graph Anomaly Detection with Pattern Mining and Feature Learning; CIKM'20: Error-bounded Graph Anomaly Loss for GNNs.

graph-data-augmentation-papers

A curated list of graph data augmentation papers.

graph2seq

Graph2Seq is a simple code for building a graph-encoder and sequence-decoder for NLP and other AI/ML/DL tasks.

graph_converter

graph_nets

PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

graphazaccess

graphgan

A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)

graphs-in-cybersecurity

Research papers utilize graph models in cybersecurity scenarios

graphsage

Representation learning on large graphs using stochastic graph convolutions.

gsat

[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

haplophysh

🎣 Using deep learning (word level and character level embeddings combined with GRU layers) to detect Phishing using the URL