Results 91 to 100 of about 1,673 (179)

Understanding and classification of innate immune response through weighted edge representation learning with dual hypergraph transformation

Results in Engineering
Existing immunology approaches for modeling peptide-human leukocyte antigen (HLA) interactions predominantly rely on traditional machine learning and convolutional neural networks.
Mallikharjuna Rao Sakhamuri, Shagufta Henna, Leo Creedon, Kevin Meehan, Marion McAfee   +4 more
doaj   +1 more source

Multimodal Feature Fusion Based Hypergraph Learning Model. [PDF]

Comput Intell Neurosci, 2022
Yang Z, Xu L, Zhao L.
europepmc   +1 more source

Causal-aware spatio-temporal hypergraph learning for early health risk prediction in community elderly care

Alexandria Engineering Journal
As the global population ages, community-based healthcare systems increasingly rely on early identification of health risks to prevent acute events and maintain quality of life for older adults.
Zheng Fang
doaj   +1 more source

Cost-Sensitive Uncertainty Hypergraph Learning for Identification of Lymph Node Involvement With CT Imaging. [PDF]

Front Med (Lausanne), 2022
Ma Q, Yan J, Zhang J, Yu Q, Zhao Y, Liang C, Di D.   +6 more
europepmc   +1 more source

Cross-scale hypergraph contrastive clustering

Journal of King Saud University: Computer and Information Sciences
Hypergraphs have demonstrated remarkable advantages in numerous fields due to their capability to model multi-way correlations among an arbitrary number of vertices in complex data.
Yuan Liu, Junxiu An, Yuze Ding
doaj   +1 more source

VLSI Hypergraph Partitioning with Deep Learning

CoRR
Partitioning is a known problem in computer science and is critical in chip design workflows, as advancements in this area can significantly influence design quality and efficiency. Deep Learning (DL) techniques, particularly those involving Graph Neural Networks (GNNs), have demonstrated strong performance in various node, edge, and graph prediction ...
Muhammad Hadir Khan, Bugra Onal, Eren Dogan, Matthew R. Guthaus   +3 more
openaire   +2 more sources

MiRNA-disease association prediction via hypergraph learning based on high-dimensionality features. [PDF]

BMC Med Inform Decis Mak, 2021
Wang YT, Wu QW, Gao Z, Ni JC, Zheng CH.
europepmc   +1 more source

Revisiting Clique and Star Expansions in Hypergraph Representation Learning: Observations, Problems, and Solutions

IEEE Access
Hypergraph representation learning has gained increasing attention for modeling higher-order relationships beyond pairwise interactions. Among existing approaches, clique expansion-based (CE-based) and star expansion-based (SE-based) methods are two ...
David Yoon Suk Kang, Eujeanne Kim, Kyungsik Han, Sang-Wook Kim   +3 more
doaj   +1 more source

LévyHyper: A Lévy Process-Driven Dynamic Hypergraph Framework for Stock Return Prediction with Jump-Aware Temporal Modeling

Mathematics
Stock return prediction for quantitative trading in U.S. equity markets has evolved from parametric econometric modeling toward data-driven deep learning systems that must jointly capture temporal dynamics, discontinuous jumps, and evolving cross-asset ...
Siyu Luo, Junming Chen
doaj   +1 more source

A novel Mamba-hypergraph enhanced time-frequency fusion network for multivariate time series classification

Complex & Intelligent Systems
Multivariate time series (MTS) classification is a crucial research area with broad applications in action recognition, healthcare, and system monitoring.
Jianjian Jiang, Chuxin Zhuang, Fangyan Lei, Ziwei Chen, Lintao Xiao, Minjing Liang, Jianfeng Peng   +6 more
doaj   +1 more source