Results 101 to 110 of about 9,987 (195)

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

A general hypergraph learning algorithm for drug multi-task predictions in micro-to-macro biomedical networks. [PDF]

PLoS Comput Biol, 2023
Jin S, Hong Y, Zeng L, Jiang Y, Lin Y, Wei L, Yu Z, Zeng X, Liu X.   +8 more
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

Cross-view contrastive learning and multi-channel hypergraph convolution for session-based recommendation

Dianxin kexue
Session-based recommendation predicts the next interaction item by analyzing anonymous users’ historical interaction data. Because of the sparsity of user behavior data, modeling session representations from a single perspective may fail to fully capture
REN Yubin, WANG Ruiqin, SUI Xinyi, FANG Chi   +3 more
doaj  

Teasing out missing reactions in genome-scale metabolic networks through hypergraph learning. [PDF]

Nat Commun, 2023
Chen C, Liao C, Liu YY.
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

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

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

Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval Hashing

Mathematics
To address modality heterogeneity and accelerate large-scale retrieval, cross-modal hashing strategies generate compact binary codes that enhance computational efficiency.
Hongyu Lin, Shaofeng Shen, Yuchen Zhang, Renwei Xia   +3 more
doaj   +1 more source