Zobrazeno 1 - 10
of 1 345
pro vyhledávání: '"Liu Yunhui"'
Publikováno v:
He jishu, Vol 47, Iss 6, Pp 060604-060604 (2024)
BackgroundCAT-1 (China Astro-Torus 1) is a levitated dipole field magnetic confinement device, which mainly used for dipole plasma physics experiments, requiring a central floating superconducting coil to be stably levitated for at least 5 h without
Externí odkaz:
https://doaj.org/article/129dd6f55abb4572b542443681de0ecf
Publikováno v:
He jishu, Vol 47, Iss 4, Pp 040504-040504 (2024)
BackgroundWhen the suspended dipole field coils experience significant disturbances during the operation of the suspended dipole field device, the Tilt-Slide-Rotate (TSR) coils are used to control the attitude of the dipole field coils, thereby preve
Externí odkaz:
https://doaj.org/article/4245d41e5c1f4a19ab5c8e6e07efc457
Heterogeneous Text-Attributed Graphs (HTAGs), where different types of entities are not only associated with texts but also connected by diverse relationships, have gained widespread popularity and application across various domains. However, current
Externí odkaz:
http://arxiv.org/abs/2412.08937
Heterogeneous Graph Neural Networks (HGNNs) have achieved promising results in various heterogeneous graph learning tasks, owing to their superiority in capturing the intricate relationships and diverse relational semantics inherent in heterogeneous
Externí odkaz:
http://arxiv.org/abs/2411.14035
Graph Contrastive Learning (GCL) has recently emerged as a promising graph self-supervised learning framework for learning discriminative node representations without labels. The widely adopted objective function of GCL benefits from two key properti
Externí odkaz:
http://arxiv.org/abs/2411.01157
In autonomous driving, there is growing interest in end-to-end online vectorized map perception in bird's-eye-view (BEV) space, with an expectation that it could replace traditional high-cost offline high-definition (HD) maps. However, the accuracy a
Externí odkaz:
http://arxiv.org/abs/2409.00620
Scale-aware monocular depth estimation poses a significant challenge in computer-aided endoscopic navigation. However, existing depth estimation methods that do not consider the geometric priors struggle to learn the absolute scale from training with
Externí odkaz:
http://arxiv.org/abs/2408.07266
Attributed graph clustering, which aims to group the nodes of an attributed graph into disjoint clusters, has made promising advancements in recent years. However, most existing methods face challenges when applied to large graphs due to the expensiv
Externí odkaz:
http://arxiv.org/abs/2408.05765
Contrastive learning is a significant paradigm in graph self-supervised learning. However, it requires negative samples to prevent model collapse and learn discriminative representations. These negative samples inevitably lead to heavy computation, m
Externí odkaz:
http://arxiv.org/abs/2408.05087
Graph clustering, which involves the partitioning of nodes within a graph into disjoint clusters, holds significant importance for numerous subsequent applications. Recently, contrastive learning, known for utilizing supervisory information, has demo
Externí odkaz:
http://arxiv.org/abs/2408.03765