Results 31 to 40 of about 5,998 (189)
Hierarchical Hypergraph-based Attention Neural Network for Service Recommendation [PDF]
Jisuanji kexueWith the rapid growth of various services and APIs on the Internet and the Web,it has become increasingly challenging for developers to quickly and accurately find APIs that meet their needs,thus requiring an efficient recommendation system.Currently,the
YANG Dongsheng, WANG Guiling, ZHENG Xin
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Multi-Order Hypergraph Convolutional Neural Network for Dynamic Social Recommendation System
IEEE Access, 2022 Recently, online social networks have enriched the users’ lives greatly and social recommendation systems make it easier for users to discover more information that they are interested in.
Yu Wang, Qilong Zhao
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Molecular hypergraph neural networks
The Journal of Chemical PhysicsGraph neural networks (GNNs) have demonstrated promising performance across various chemistry-related tasks. However, conventional graphs only model the pairwise connectivity in molecules, failing to adequately represent higher order connections, such as multi-center bonds and conjugated structures.
Junwu Chen, Philippe Schwaller
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Node Classification Method Based on Hierarchical Hypergraph Neural Network
SensorsHypergraph neural networks have gained widespread attention due to their effectiveness in handling graph-structured data with complex relationships and multi-dimensional interactions.
Feng Xu +3 more
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Consistency of Spectral Hypergraph Partitioning under Planted Partition Model
, 2016 Hypergraph partitioning lies at the heart of a number of problems in machine learning and network sciences. Many algorithms for hypergraph partitioning have been proposed that extend standard approaches for graph partitioning to the case of hypergraphs ...
Dukkipati, Ambedkar +1 more
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Hyper-Ordinal Pattern: Measuring High-Order Connection Relationship in Brain Disease Networks
IEEE Transactions on Neural Systems and Rehabilitation EngineeringBrain hyper-networks as a kind of hypergraph for brain network analysis, describing the high-order interactions among brain regions, have been extensively utilized in research on brain diseases such as mild cognitive impairment (MCI) and Alzheimer’
Tianyu Du +3 more
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AI Open, 2023 Stock price prediction is challenging in financial investment, with the AI boom leading to increased interest from researchers. Despite these recent advances, many studies are limited to capturing the time series characteristics of price movement via ...
Zhongtian Sun +4 more
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Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Advanced Science, EarlyView.Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
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Structural Deep Embedding for Hyper-Networks
, 2018 Network embedding has recently attracted lots of attentions in data mining. Existing network embedding methods mainly focus on networks with pairwise relationships. In real world, however, the relationships among data points could go beyond pairwise, i.e.
Cui, Peng +4 more
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Advanced Intelligent Discovery, EarlyView.This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
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