Abstract: Accurate and real-time traffic forecasting plays an important role in the intelligent traffic system and is of great significance for urban traffic planning, traffic management, and traffic ...

Abstract: Graph convolutional networks (GCNs) have attracted considerable interest in skeleton-based action recognition. Existing GCN-based models have proposed methods to learn dynamic graph ...

PyTorch version should be 0.3! For PyTorch0.4 or higher, the codes need to be modified. Now we have updated the code to >=Pytorch0.4. A new model named AAGCN is added, which can achieve better ...

This repo contains an example implementation of the Simple Graph Convolution (SGC) model, described in the ICML2019 paper Simplifying Graph Convolutional Networks. SGC removes the nonlinearities and ...

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...

Sub-headline: HUST researchers systematize SNA methods, building an evolutionary taxonomy based on graph representation ...

Researchers have developed an artificial intelligence model that predicts crime more accurately than several existing ...

Spread the love“`html Understanding how to create a neural network can be a game-changer in the fields of artificial intelligence and machine learning. As industries increasingly rely on data-driven ...

Digestive system cancers, including hepatobiliary and gastrointestinal malignancies, remain a major global oncological burden ...

课程特别引入大语言模型（LLM）辅助科研新范式，从Ollama本地部署到LangChain射频智能体开发，帮助学员掌握AI Agent构建方法，推动射频信号智能处理技术向自动化、精准化、自适应方向发展。 核心目标：系统学习射频数据集的构建方法，掌握CNN、LSTM、Transformer ...