Cloud vendors are actively adopting FPGAs into their infrastructures for enhancing
performance and efficiency. As cloud services continue to evolve, FPGA (field …

Graph analytics, which mainly includes graph processing, graph mining, and graph learning,
has become increasingly important in several domains, including social network analysis …

Graph neural networks (GNNs) are powerful models capable of managing intricate
connections in non-Euclidean data, such as social networks, physical systems, chemical …

In the past two years, various graph convolution neural networks (GCNs) accelerators have
emerged, each with their own characteristics, but their common disadvantage is that the …

Graph convolutional networks (GCNs) have been successfully applied to many fields such
as social networks, knowledge graphs, and recommend systems. The purpose of this …

Despite the extraordinary applicative potentiality that dynamic graph inference may entail, its
practical-physical implementation has been a topic seldom explored in literature. Although …

Pedestrian trajectory prediction is a critical technology in the evolution of self-driving cars
toward complete artificial intelligence. Over recent years, focusing on the trajectories of …

针对传统Android 恶意程序检测方法无法解决的伪装及实时检测问题, 提出了一种基于异构信息
网络的Android 恶意程序检测方法. 将Android 实体及关系建模为异构信息网络中的节点和边 …

Deep learning brings good prospects for the development of AI, but the complexity and slow
operation of deep learning algorithms hinder the development and application of deep …