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Tech Xplore on MSN7d
Novel out-of-core mechanism introduced for large-scale graph neural network training
A research team has introduced a new out-of-core mechanism, Capsule, for large-scale GNN training, which can achieve up to a ...
Design-Reuse15d
Placement of different type nodes in a Network-on-chip graph
St. Petersburg University of Aerospace Instrumentation. For system tasks we could form a rate of messages flows between nodes of different type’s matrix L. The value of element Lij of this matrix is ...
IEEE25d
GTAE-IDS: Graph Transformer-Based Autoencoder Framework for Real-Time Network Intrusion Detection
We propose GTAE-IDS, a novel unsupervised packet-based graph neural network framework aimed at early and precise anomaly detection in network traffic. GTAE-IDS employs graph embeddings to capture and ...
IEEE24d
Partially-Supervised Graph Derivation Network with Meta-Learning for Time Series Anomaly Detection
In this paper, we propose a novel approach called the Partially-Supervised Graph Derivation Network with Meta Learning (PS-GDNML) for time series anomaly detection. PS-GDNML combines the power of ...
GitHub10d
Network Analysis Made Simple
Welcome to the GitHub repository for Network Analysis Made Simple! This is a tutorial designed to teach you the basic and practical aspects of graph theory. It has been presented at multiple ...
GitHub12d
Graphical Contrastive Losses for Scene Graph Parsing
Results of "Graph-RCNN" are directly copied from ... An easy installation if you already have Anaconda Python 3 and CUDA 9.0: conda install pytorch=0.4.1 pip install cython pip install matplotlib ...
LinkedIn18d
Royson Pais’ Post
Master Python Network Automation - Live Demo 🚀 🔹 Are you ready to take your networking skills to the next level? Join us for an exclusive live demo on Python Network Automation, where you'll ...