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Researchers Propose a Novel Representation Learning Framework to Address the Lack of Causal Characterization in Deep Learning Models

Recently, researchers introduced a new representation learning framework that integrates causal inference with graph neural networks—CauSkelNet, which can be used to model the causal relationships and ...

Huiyou Jiahua Applies for Logistics Demand Forecasting Patent Based on Spatio-Temporal Graph Convolutional Network Technology to Improve Prediction Accuracy

Spatio-Temporal Graph Convolutional Network Huiyou Jiahua's patent employs spatio-temporal graph convolutional network technology, marking a significant technological breakthrough in the field of ...

Yixin Zhou Advances Industrial Intelligence with AI-Based Anomaly Detection Model

A high-performance AI framework enhances anomaly detection in industrial systems using optimized Graph Deviation Networks and graph attention ...