LEADER 04398nam 22007455 450 001 996546850903316 005 20230823133417.0 010 $a3-031-42795-5 024 7 $a10.1007/978-3-031-42795-4 035 $a(MiAaPQ)EBC30719881 035 $a(Au-PeEL)EBL30719881 035 $a(DE-He213)978-3-031-42795-4 035 $a(PPN)272260460 035 $a(EXLCZ)9928044443200041 100 $a20230823d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aGraph-Based Representations in Pattern Recognition$b[electronic resource] $e13th IAPR-TC-15 International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September 6?8, 2023, Proceedings /$fedited by Mario Vento, Pasquale Foggia, Donatello Conte, Vincenzo Carletti 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (193 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v14121 311 08$aPrint version: Vento, Mario Graph-Based Representations in Pattern Recognition Cham : Springer,c2023 9783031427947 320 $aIncludes bibliographical references and index. 327 $aGraph 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 Autoencoders for 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. 330 $aThis book constitutes the refereed proceedings of the 13th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2023, which took place in Vietri sul Mare, Italy, in September 2023. The 16 full papers included in this book were carefully reviewed and selected from 18 submissions. 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Introduction: Causation in Social-Ecological Systems -- Part I: Semantics of causal expressions -- Chapter 2. Causal Talk Permeates Ordinary Language -- Chapter 3. Causal Talk is Fundamental -- Chapter 4. Causation, Counterfactual Dependence and Potential Outcomes -- Part II: Causation in Science -- Chapter 5. Causal Relations and Causal Relata in Science -- Chapter 6. Causation, Laws and Regularities -- Chapter 7. Inferences from Statistics to Causation -- Chapter 8. Causal Explanations -- Part III: Causation in Complex SES -- Chapter 9. Causation in Social-Ecological Systems Research -- Part IV: Appendices -- A How Does a Theory Relate to Reality? -- B Models -- C. Confidence Intervals and Correlations. 330 $aThis open access book is about causal thinking and the use of causal language, with a focus on introducing philosophical ideas about causation to students and researchers of Social-Ecological Systems (SES). 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