A list of recent papers about Graph Neural Network methods applied in NLP areas.
This project focuses on predicting maternal-fetal health outcomes, specifically early detection of preeclampsia, by learning transferable representations from cfRNA and placental transcriptomic data.
Time-Relaxed Directed GNN for Bitcoin Fraud Detection | 6 Novel Contributions | Production-Ready | E7-A3: 0.5846 PR-AUC (+4.1%) | E9 Fusion: +33.5% | Publication-Ready Research
PyTorch implementation of Heterogeneous Graph Neural Networks with attention aggregation for node classification on academic networks.
ConHGNN-SUM: Contextualized Heterogeneous Graph Neural Networks for extractive document summarization. Published in IEEE AISP 2024. Revolutionizes summarization by modeling documents as dynamic graphs with semantic relationships between words and sentences.
🕐 Uncover Bitcoin fraud with our zero-leakage temporal GNN, designed for effective detection through a systematic, experimental approach.
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