IEEE

Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity

Abstract: The success of graph neural networks (GNNs) in graph-based web mining highly relies on abundant human-annotated data, which is laborious to obtain in practice. When only a few labeled nodes ...
IEEE

From Cluster Assumption to Graph Convolution: Graph-Based Semi-Supervised Learning Revisited

Abstract: Graph-based semi-supervised learning (GSSL) has long been a research focus. Traditional methods are generally shallow learners, based on the cluster assumption. Recently, graph convolutional ...
GitHub

Unified Parallel Semantic Log Parsing based on Causal Graph Construction for Attack Attribution

# avoid python version conflict --- pyenv brew install pyenv-virtualenv brew install pyenv pyenv install 3.10 pyenv global 3.10 pyenv virtualenv 3.10 UTLParser ...
Semiconductor Engineering

ONNX And Python To C++: State-Of-The-Art Graph Compilation

Nigel Drego, Co-founder and Chief Technology Officer at Quadric, presented the “ONNX and Python to C++: State-of-the-art Graph Compilation” tutorial at this year’s Embedded Vision Summit. Quadric’s ...
GitHub

GCN for Node Classification with PyTorch Geometric

This repository contains a Jupyter Notebook that implements a Graph Convolutional Network (GCN) for semi-supervised node classification. The project uses the PyTorch Geometric (PyG) library to build ...
Scientific Research Publishing

Analysis of Production Decline Rate to Predict the Life Span of Mnazibay Gas Field ()

Isaac, L. , Ndunguru, C. and Nsulangi, P. (2025) Analysis of Production Decline Rate to Predict the Life Span of Mnazibay Gas ...