Vento / Foggia / Conte Graph-Based Representations in Pattern Recognition
1. Auflage 2023
ISBN: 978-3-031-42795-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
13th IAPR-TC-15 International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September 6–8, 2023, Proceedings
E-Book, Englisch, 184 Seiten
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-031-42795-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
The 16 full papers included in this book were carefully reviewed and selected from 18 submissions. They were organized in topical sections on graph kernels and graph algorithms; graph neural networks; and graph-based representations and applications.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Graph Kernels and Graph Algorithms.- Quadratic Kernel Learning for Interpolation Kernel Machine Based Graph Classification.- Minimum Spanning Set Selection in Graph Kernels.- Graph-based vs. Vector-based Classification: A Fair Comparison.- A Practical Algorithm for Max-Norm Optimal Binary Labeling of Graphs.- Efficient Entropy-based Graph Kernel.- Graph Neural Networks.- GNN-DES: A new end-to-end dynamic ensemble selection method based on multi-label graph neural network.- C2N-ABDP: Cluster-to-Node Attention-based Differentiable Pooling.- Splitting Structural and Semantic Knowledge in Graph Autoencodersfor Graph Regression.- Graph Normalizing Flows to Pre-image Free Machine Learning for Regression.- Matching-Graphs for Building Classification Ensembles.- Maximal Independent Sets for Pooling in Graph Neural Networks.- Graph-based Representations and Applications.- Detecting Abnormal Communication Patterns in IoT Networks Using Graph Neural Networks.- Cell segmentation of in situ transcriptomics data using signed graph partitioning.- Graph-based representation for multi-image super-resolution.- Reducing the Computational Complexity of the Eccentricity Transform.- Graph-Based Deep Learning on the Swiss River Network.
