A comfortable graph structure for Grover walk
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Physics A: Mathematical and Theoretical"
DOI: 10.1088/1751-8121/acd735
Abstract: We consider a Grover walk model on a finite internal graph, which is connected with a finite number of semi-infinite length paths and receives the alternative inflows along these paths at each time step. After… read more here.
Keywords: grover walk; internal graph; graph; comfortable graph ... See more keywords
Learning representations for gene ontology terms by jointly encoding graph structure and textual node descriptors
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac318
Abstract: Measuring the semantic similarity between Gene Ontology (GO) terms is a fundamental step in numerous functional bioinformatics applications. To fully exploit the metadata of GO terms, word embedding-based methods have been proposed recently to map… read more here.
Keywords: structure; encoding graph; ontology; gene ontology ... See more keywords
Generative Service Provisioning for IoT Devices Using Line Graph Structure
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3244890
Abstract: A service subgraph helps Internet-of-Things devices access resources in a dynamic Internet-of-Things device network. We propose a service subgraph generation method for Internet-of-Things device networks. Service subgraph generation aims to find more capable neighboring Internet-of-Things… read more here.
Keywords: service provisioning; service subgraph; service; line graph ... See more keywords
Hyperspectral Image Classification Based on Superpixel Feature Subdivision and Adaptive Graph Structure
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3153446
Abstract: The graph-based hyperspectral image classification (HSIC) method has attracted wide attention because it can extract information with a non-Euclidean structure. Many graph-based HSIC works have achieved good results, but unresolved technical issues remain. For example,… read more here.
Keywords: structure; graph structure; classification; graph ... See more keywords
Refining Graph Structure for Incomplete Multi-View Clustering.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3189763
Abstract: As a challenging problem, incomplete multi-view clustering (MVC) has drawn much attention in recent years. Most of the existing methods contain the feature recovering step inevitably to obtain the clustering result of incomplete multi-view datasets.… read more here.
Keywords: graph; incomplete multi; graph structure; multi view ... See more keywords
Homophily-Enhanced Self-Supervision for Graph Structure Learning: Insights and Directions.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2023.3257325
Abstract: Graph neural networks (GNNs) have recently achieved remarkable success on a variety of graph-related tasks, while such success relies heavily on a given graph structure that may not always be available in real-world applications. To… read more here.
Keywords: graph structure; enhanced self; supervision; graph ... See more keywords
Unsupervised Graph Embedding via Adaptive Graph Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3202158
Abstract: Graph autoencoders (GAEs) are powerful tools in representation learning for graph embedding. However, the performance of GAEs is very dependent on the quality of the graph structure, i.e., of the adjacency matrix. In other words,… read more here.
Keywords: embedding via; unsupervised graph; graph; graph embedding ... See more keywords
A Plant Disease Recognition Method Based on Fusion of Images and Graph Structure Text
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Plant Science"
DOI: 10.3389/fpls.2021.731688
Abstract: The disease image recognition models based on deep learning have achieved relative success under limited and restricted conditions, but such models are generally subjected to the shortcoming of weak robustness. The model accuracy would decrease… read more here.
Keywords: disease recognition; disease; graph structure; structure text ... See more keywords
Generic Structure Extraction with Bi-Level Optimization for Graph Structure Learning
Sign Up to like & getrecommendations! Published in 2022 at "Entropy"
DOI: 10.3390/e24091228
Abstract: Currently, most Graph Structure Learning (GSL) methods, as a means of learning graph structure, improve the robustness of GNN merely from a local view by considering the local information related to each edge and indiscriminately… read more here.
Keywords: structure; structure learning; graph structure; level ... See more keywords
Deeper Exploiting Graph Structure Information by Discrete Ricci Curvature in a Graph Transformer
Sign Up to like & getrecommendations! Published in 2023 at "Entropy"
DOI: 10.3390/e25060885
Abstract: Graph-structured data, operating as an abstraction of data containing nodes and interactions between nodes, is pervasive in the real world. There are numerous ways dedicated to extract graph structure information explicitly or implicitly, but whether… read more here.
Keywords: information; structure; structure information; curvature ... See more keywords