Abstract: The spatiotemporal dynamics of traffic forecasting make it a challenging task. In recent years, by adapting to the topology of traffic networks where road segments serve as nodes, graph ...

Abstract: Recent advances in deep learning-based signal re-representation methods have achieved significant breakthroughs in tasks like signal modulation recognition. In this paper, we propose a ...

Encode entities and relations in a knowledge graph using an RGCN-based GNN encoder Formulate learning path planning as a sequential decision-making problem Apply reinforcement learning to guide path ...

This project implements a Convolutional Autoencoder trained on the MNIST handwritten‐digits dataset. The goal is to learn compact latent representations of the input images and to reconstruct them ...

Artificial intelligence–generated content (AIGC) has shown remarkable performance in nuclear medicine imaging (NMI), offering cost-effective software solutions for tasks such as image enhancement, ...