IEEE

A Hybrid Graph Neural Network and Neural ODE Model to Intrusion Detection in Dynamic ...

Abstract: The adaptive nature of evolving cyber-threats, particularly in Internet of Things (IoT) and Software-Defined Networking (SDN) environments, necessitates intrusion detection systems (IDS) ...
IEEE

RandomViG: Random Vision Graph Neural Network for Image Classification

Abstract: Vision Graph Neural Network (ViG) is the first graph neural network model capable of directly processing image data. The community primarily focuses on the model structures to improve ViG’s ...
来自MSN

Backpropagation from scratch in Python – step by step neural network tutorial

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
来自MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
GitHub

Causal Feature-aware Dynamic Graph Neural Network for Open-Set Domain Generalization ...

This paper has been accepted for publication in Advanced Engineering Informatics. The following papers were used as references for this code. TodyNet: Temporal dynamic graph neural network for ...