Zobrazeno 1 - 10
of 2 053
pro vyhledávání: '"Heterogeneous graph neural network"'
Autor:
Wang, Zihuan, Wong, Vincent W. S.
Integrated sensing and communication (ISAC) is one of the usage scenarios for the sixth generation (6G) wireless networks. In this paper, we study cooperative ISAC in cell-free multiple-input multiple-output (MIMO) systems, where multiple MIMO access
Externí odkaz:
http://arxiv.org/abs/2410.09963
We present a Morphology-Informed Heterogeneous Graph Neural Network (MI-HGNN) for learning-based contact perception. The architecture and connectivity of the MI-HGNN are constructed from the robot morphology, in which nodes and edges are robot joints
Externí odkaz:
http://arxiv.org/abs/2409.11146
In the rapidly evolving field of cybersecurity, the integration of flow-level and packet-level information for real-time intrusion detection remains a largely untapped area of research. This paper introduces "XG-NID," a novel framework that, to the b
Externí odkaz:
http://arxiv.org/abs/2408.16021
Autor:
Li, Yang1 (AUTHOR) 2023322030139@mail.ncut.edu.cn, Yan, Shichao1 (AUTHOR), Zhao, Fangtao1 (AUTHOR), Jiang, Yi1 (AUTHOR), Chen, Shuai1 (AUTHOR), Wang, Lei2 (AUTHOR), Ma, Li1 (AUTHOR)
Publikováno v:
Future Internet. Aug2024, Vol. 16 Issue 8, p270. 20p.
Existing heterogeneous graph neural network algorithms (HGNNs) mostly rely on meta-paths to capture the rich semantic information contained in heterogeneous graphs (also known as heterogeneous information networks (HINs)), but most of these HGNNs foc
Externí odkaz:
http://arxiv.org/abs/2405.18933
Publikováno v:
published at ICASSP 2024
Conversational Emotion Recognition (CER) aims to predict the emotion expressed by an utterance (referred to as an ``event'') during a conversation. Existing graph-based methods mainly focus on event interactions to comprehend the conversational conte
Externí odkaz:
http://arxiv.org/abs/2405.03960
In next-generation communications, sub-6GHz and millimeter-wave (mmWave) links typically coexist, with the sub-6GHz link always active and the mmWave link active when high-rate transmission is required. Due to the spatial similarities between sub-6GH
Externí odkaz:
http://arxiv.org/abs/2404.17138
Predicting Remaining Useful Life (RUL) plays a crucial role in the prognostics and health management of industrial systems that involve a variety of interrelated sensors. Given a constant stream of time series sensory data from such systems, deep lea
Externí odkaz:
http://arxiv.org/abs/2405.04336
Heterogeneous graphs are ubiquitous to model complex data. There are urgent needs on powerful heterogeneous graph neural networks to effectively support important applications. We identify a potential semantic mixing issue in existing message passing
Externí odkaz:
http://arxiv.org/abs/2405.01927
Many computer vision and machine learning problems are modelled as learning tasks on heterogeneous graphs, featuring a wide array of relations from diverse types of nodes and edges. Heterogeneous graph neural networks (HGNNs) stand out as a promising
Externí odkaz:
http://arxiv.org/abs/2403.08207