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pro vyhledávání: '"Kim, Chong A"'
Traditional Graph Neural Networks (GNNs) rely on network homophily, which can lead to performance degradation due to over-smoothing in many real-world heterophily scenarios. Recent studies analyze the smoothing effect (separability) after message-pas
Externí odkaz:
http://arxiv.org/abs/2408.04895
Autonomous off-road navigation requires an accurate semantic understanding of the environment, often converted into a bird's-eye view (BEV) representation for various downstream tasks. While learning-based methods have shown success in generating loc
Externí odkaz:
http://arxiv.org/abs/2403.02642
As an alternative approach to ionic data transmission with hydrogel as substrate, this work explores the possible applications of liquid electrolyte filling cavity of a stretchable, flexible elastomeric tubing, which is the primary ingredient used in
Externí odkaz:
http://arxiv.org/abs/2307.01722
Graph Neural Networks (GNNs) have proven to be powerful in many graph-based applications. However, they fail to generalize well under heterophilic setups, where neighbor nodes have different labels. To address this challenge, we employ a confidence r
Externí odkaz:
http://arxiv.org/abs/2302.09755
Message-passing Graph Neural Networks (GNNs), which collect information from adjacent nodes achieve dismal performance on heterophilic graphs. Various schemes have been proposed to solve this problem, and propagating signed information on heterophili
Externí odkaz:
http://arxiv.org/abs/2301.08918
Graph contrastive learning has become a powerful technique for several graph mining tasks. It learns discriminative representation from different perspectives of augmented graphs. Ubiquitous in our daily life, singed-directed graphs are the most comp
Externí odkaz:
http://arxiv.org/abs/2301.05163
Autor:
Yeo, Jung-Hyun1 (AUTHOR) 24022702@a.ut.ac.kr, Kim, Chong-Eun2 (AUTHOR) cekim@ut.ac.kr
Publikováno v:
Energies (19961073). Dec2024, Vol. 17 Issue 24, p6262. 14p.
Graph neural networks (GNNs) are commonly used in semi-supervised settings. Previous research has primarily focused on finding appropriate graph filters (e.g. aggregation methods) to perform well on both homophilic and heterophilic graphs. While thes
Externí odkaz:
http://arxiv.org/abs/2211.15081
Autor:
Ko, Taewook, Kim, Chong-Kwon
A signed directed graph is a graph with sign and direction information on the edges. Even though signed directed graphs are more informative than unsigned or undirected graphs, they are more complicated to analyze and have received less research atte
Externí odkaz:
http://arxiv.org/abs/2208.11511
Publikováno v:
In Journal of Biological Chemistry December 2024 300(12)