Tag: Release

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S-CGIB, A Novel Pre-trained Graph Neural Network in Molecular Structure Learning

The Network Science Lab at the Catholic University of Korea releases S-CGIB, a Novel Pre-trained Graph Neural Network in Molecular Structure Learning

CART, A Novel Kiosk Recommendation System for Offline Retail Environment

The Network Science Lab at the Catholic University of Korea releases Context-Aware Residual Transformer, namely CART, a novel transformer-based recommendation system specialised in offline retail environment.

CGT, A Novel Graph Transformer Model for Mitigating Degree Biases in Message Passing Mechanism

The Network Science Lab at the Catholic University of Korea releases Community-aware Graph Transformers, namely CGT, a novel Graph Transformer model specialised in mitigating degree biases in message passing mechanism.

LiteralKG, A Novel GNN Model for Learning Literal-aware Representations of Medical Knowledge Graphs

The Network Science Lab at the Catholic University of Korea releases LiteralKG, a novel GNN model for learning literal-aware representations of medical knowledge graphs to integrate literal information and graph structural features into unified vector representations.

UGT, A Novel Graph Transformer Model for Unifying Local and Global Graph Structural Features

The Network Science Lab at the Catholic University of Korea releases UGT, a novel Graph Transformer model specialised in preserving both local and global graph structures.

Connector, A Unified Framework for Graph Representation Learning

The Network Science Lab at the Catholic University of Korea releases Connector, a comprehensive graph representation learning framework developed primarily in Python using the PyTorch library.