Nature

Graph autoencoder with mirror temporal convolutional networks for traffic anomaly detection

In recent years, intelligent transportation have become increasingly complex due to rapid urbanization and population growth. There is a growing need for abnormal event detection in transportation ...
Nature

AAGCN: a graph convolutional neural network with adaptive feature and topology learning

In recent years, there has been a growing prevalence of deep learning in various domains, owing to advancements in information technology and computing power. Graph neural network methods within deep ...
IEEE

3D Human Pose Estimation with Two-Step MixedGraph Convolution Transformer Encoder

Abstract: In 3D human pose estimation, human joints typically exhibit continuity and interdependence during motion, suggesting that joint velocities and their positional relationships can offer ...
IEEE

GDetox: Purifying Backdoor Encoder in Graph Self-Supervised Learning via Knowledge Distillation

Abstract: Graph Neural Networks (GNNs) have powerful representation capabilities for graph data, achieving excellent performance across various fields. Considering the scarcity of labels in real-world ...
GitHub

Physics-Informed Graph Attention Network with Temporal Convolutional Encoder for Multi-Node Distribution Grid State Forecasting under Solar PV Uncertainty

There's not enough diversity for attention to learn meaningful patterns Uniform averaging is near-optimal when all neighbors matter equally Attention adds noise rather than extracting signal Despite ...
GitHub

go_graph_encoder.py

Use create_go_graph_encoder_pipeline(unified_go_encoder=True/False) to choose architecture.
LinkedIn

Convolution and Transformer Encoder Neural Network for Heart Sound Classification

📢 📢 📢 Heart Sound Classification Network Based on Convolution and Transformer 🧑🔬 Jiawen Cheng and Kexue Sun 🏫 Nanjing University of Posts and Telecommunications; Nation-Local Joint Project ...