Results 121 to 130 of about 6,572,416 (223)

MSCDGCN: Multi-scale central difference graph convolution network for skeleton-based action recognition

Journal of King Saud University: Computer and Information Sciences
Effectively distinguishing fine-grained actions remains a critical challenge in skeleton-based action recognition. Existing Graph Convolutional Network methods often overlook directional motion cues and fail to integrate spatiotemporal features ...
Xinlu Zong, Siyu Dong, Jiawei Guo
doaj   +1 more source

Application of Graph Theory for Blockchain Technologies

Mathematics
Blockchain technology, serving as the backbone for decentralized systems, facilitates secure and transparent transactional data storage across a distributed network of nodes.
Guruprakash Jayabalasamy, Cyril Pujol, Krithika Latha Bhaskaran   +2 more
doaj   +1 more source

Centrally symmetric graphs [PDF]

Czechoslovak Mathematical Journal, 1968
openaire   +1 more source

Graph theory inspired anomaly detection at the LHC

Journal of High Energy Physics
Designing model-independent anomaly detection algorithms for analyzing LHC data remains a central challenge in the search for new physics, due to the high dimensionality of collider events. In this work, we develop a graph autoencoder as an unsupervised,
Jack Y. Araz, Dimitrios Athanasakos, Mateusz Ploskon, Felix Ringer   +3 more
doaj   +1 more source

Central Cycles in Graphs

Central Cycles in Graphs
application/pdf ...
openaire  

A channel water temperature prediction method based on transfer learning and spatial-temporal graph neural networks. [PDF]

Sci Rep
Lu H, Tian Y, Weng P, Qiao Y.
europepmc   +1 more source

Obstructive shock caused by infection of a mediastinal tumor: a case report and literature review. [PDF]

Front Med (Lausanne)
Wang W, Cheng L, Hu X, Wan H, Pan C.
europepmc   +1 more source

KANPM-DTA: improving drug-target affinity prediction with Kolmogorov-Arnold networks and pretrained models. [PDF]

Brief Bioinform
Rakib MDYK, Alamin MH, Li J, Mamun SS, Gobena KA, Ren S.   +5 more
europepmc   +1 more source

AI-powered TargetMap: Enabling system-level target discovery through full-path reasoning on a unified knowledge graph. [PDF]

iScience
Jin X, Wang S, Chen J, Shen S, Yan F, Wu J, He Q, Xu H, Wu R, Cao J, Yang B.   +10 more
europepmc   +1 more source

Desiderata for a biomedical knowledge network: opportunities, challenges and future directions. [PDF]

Bioinform Adv
Wu C, Liu H, Flannick J, Musen MA, Su AI, Hunter LE, Powers TM, Wu CH.   +7 more
europepmc   +1 more source