NSTL国家科技图书文献中心

1. Enhancing Graph Topology and Clustering Quality: A Modularity-Guided Approach NSTL国家科技图书文献中心

Xiaotian Zhuang | Yongyu Wang ... - 《Pattern Recognition,Part X》 - International Conference on Pattern Recognition - 2025, - 131～142 - 共12页

摘要： maximize modularity within a fixed graph topology | guide the enhancement of both graph* topology and* | outperforms state-of-the-art graph* construction methods in* | to a hundredfold increase in graph* construction* | Current modularity-based community detection

关键词： Modularity | Graph | Clustering

2. Characterizing the Influence of Topology on Graph Learning Tasks NSTL国家科技图书文献中心

Kailong Wu | Yule Xie ... - 《Database Systems for Advanced Applications,Part II》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 35～50 - 共16页

摘要： understanding and analyzing how graph* topology influences the* | influence of graph* topology by measuring the level of* | Graph neural networks (GNN) have achieved | features combined with topology* to create effective* | compatibility between the topological information of graph

关键词： GNNs | Graph topology | Graph rewiring

3. Online graph topology learning from matrix-valued time series NSTL国家科技图书文献中心

Jiang, Yiye | Bigot, Jeremie ... - 《Computational statistics & data analysis》 - 2025,202 - 共36页

摘要： with a graph. When only one feature per sensor is | causal graph. The first contribution extends VAR models | to matrix-variate models for the purpose of graph | of the graph* and trend from streaming samples* | The focus is on the statistical analysis of

关键词： Graph learning | Matrix-variate data | Auto-regressive models | Homotopy algorithms

4. Parameter Identification of Power Distribution System Based on Dynamic Graph Topology NSTL国家科技图书文献中心

Zhiwei Wang | Wei Jiang ... - 《IEEE transactions on industrial informatics》 - 2025,21(2) - 1309～1318 - 共10页

摘要： distribution system, including the topology, essential | distribution system, the frequently changing topology* of the* | learning, we propose a dynamic graph* fusion network (DGFN* | ) architecture to tackle the topology* and line parameter joint* | identification problem. The DGFN model is based on the graph

关键词： Topology | Network topology | Distribution networks | Accuracy | Nearest neighbor methods | Deep learning | Voltage measurement | Decoding | Convolutional neural networks | Noise

5. Strongly Topology-Preserving GNNs for Brain Graph Super-Resolution NSTL国家科技图书文献中心

Pragya Singh | Islem Rekik - 《Predictive Intelligence in Medicine》 - International Conference on Medical Image Computing and Computer Assisted Intervention | International Workshop on Predictive Intelligence in Medicine - 2025, - 124～136 - 共13页

摘要：Brain graph* super-resolution is an under* | leverage graph* neural networks (GNNs) thanks to their* | ability to natively handle graph-structured datasets | . However, numerous studies have shown that brain graph | topology is crucial in identifying the onset and presence

关键词： Topology-preserving GNNs | Super-resolution | Primal-dual formulation

6. Graph U-Net With Topology-Feature Awareness Pooling for Hyperspectral Image Classification NSTL国家科技图书文献中心

Rong Chen | Gemine Vivone ... - 《IEEE Transactions on Geoscience and Remote Sensing》 - 2025,63 - 1～14 - 共14页

摘要： graph U-Net with topology-feature awareness pooling | pooled graph, the graphs topology* structure and node* | Nowadays, various graph* convolutional networks* | (GCNs) to process graph-structured data have been | emphasize graph node feature aggregation instead of graph

关键词： Feature extraction | Data mining | Noise measurement | Aggregates | Topology | Hyperspectral imaging | Graph convolutional networks | Fuses | Training | Support vector machines

7. Topology Derivation Method of Common-Ground Transformerless Single-Phase Inverters Based on Graph Theory NSTL国家科技图书文献中心

Zhilei Yao | Qin Xu - 《IEEE Transactions on Power Electronics》 - 2025,40(3) - 4510～4521 - 共12页

摘要： there is no systematic theory on topology* derivation* | of them. Therefore, a general topology* derivation* | based on graph* theory is proposed. The common-ground* | Common-ground transformerless single-phase | inverters are widely used in the photovoltaic generation

关键词： Inverters | Topology | Capacitors | Voltage | Inductors | Graph theory | Switches | Transformers | Leakage currents | Photovoltaic systems

8. Computer Vision-Aided RFID Tag Group Location Measurement and Reading Performance Prediction Using Graph Transformer Network With Novel Topology Graph Construction Strategy NSTL国家科技图书文献中心

Zhuang, Xiao | Sun, Weifang ... - 《IEEE Transactions on Instrumentation and Measurement》 - 2025,74(Pt.1) - 5000615.1～5000615.15 - 共15页

摘要： synergistic topology graph construction strategy using graph | topology graph construction (STGC) strategy makes up for | positions. After that, addressing the complex topology | the insensitivity of graph* attention transformer* | network (GATN) model to similar topology* structures by*

关键词： Radiofrequency identification | Topology | Network topology | Three-dimensional displays | Transformers | Optimization | Position measurement | Electromagnetics | Convolutional neural networks | Antennas...

9. A power grid topology detection method based on edge graph attention neural network NSTL国家科技图书文献中心

Zhao C. | Li X.... - 《Electric Power Systems Research》 - 2025,239(Feb.) - 1.1～1.11 - 共11页

摘要： Edge Graph* Attention Neural Network (EGAT) model* | accuracy and robustness of grid topology* detection after* | © 2024 Elsevier B.V.Against the backdrop of | growing power demand and market liberalization | , operators optimize power transmission and system load

关键词： Edge graph attention | Feature aggregation | Grid reconfiguration | Neural network | Topology detection

10. Topology Bench: systematic graph-based benchmarking for core optical networks NSTL国家科技图书文献中心

Robin Matzner | Akanksha Ahuja ... - 《Journal of optical communications and networking》 - 2025,17(1) - 7～27 - 共21页

摘要：Topology Bench is a comprehensive topology | . Topology* Bench addresses this limitation, offering a* | network topologies through the lens of graph-theoretical | approach to topology* selection. A statistical and* | of these graph* metrics and the relationships*

关键词： Topology | Network topology | Optical fiber networks | Benchmark testing | Resource management | Measurement | Synthetic data | Optical imaging | Data models | Systematics

摘要： maximize modularity within a fixed graph topology | guide the enhancement of both graph topology and | outperforms state-of-the-art graph construction methods in | to a hundredfold increase in graph construction | Current modularity-based community detection

关键词： Modularity | Graph | Clustering

摘要： understanding and analyzing how graph topology influences the | influence of graph topology by measuring the level of | Graph neural networks (GNN) have achieved | features combined with topology to create effective | compatibility between the topological information of graph

关键词： GNNs | Graph topology | Graph rewiring

摘要： with a graph. When only one feature per sensor is | causal graph. The first contribution extends VAR models | to matrix-variate models for the purpose of graph | of the graph and trend from streaming samples | The focus is on the statistical analysis of

关键词： Graph learning | Matrix-variate data | Auto-regressive models | Homotopy algorithms

关键词： Topology | Network topology | Distribution networks | Accuracy | Nearest neighbor methods | Deep learning | Voltage measurement | Decoding | Convolutional neural networks | Noise

摘要：Brain graph super-resolution is an under | leverage graph neural networks (GNNs) thanks to their | ability to natively handle graph-structured datasets | . However, numerous studies have shown that brain graph | topology is crucial in identifying the onset and presence

关键词： Topology-preserving GNNs | Super-resolution | Primal-dual formulation

摘要： graph U-Net with topology-feature awareness pooling | pooled graph, the graphs topology structure and node | Nowadays, various graph convolutional networks | (GCNs) to process graph-structured data have been | emphasize graph node feature aggregation instead of graph

关键词： Feature extraction | Data mining | Noise measurement | Aggregates | Topology | Hyperspectral imaging | Graph convolutional networks | Fuses | Training | Support vector machines

摘要： there is no systematic theory on topology derivation | of them. Therefore, a general topology derivation | based on graph theory is proposed. The common-ground | Common-ground transformerless single-phase | inverters are widely used in the photovoltaic generation

关键词： Inverters | Topology | Capacitors | Voltage | Inductors | Graph theory | Switches | Transformers | Leakage currents | Photovoltaic systems

摘要： synergistic topology graph construction strategy using graph | topology graph construction (STGC) strategy makes up for | positions. After that, addressing the complex topology | the insensitivity of graph attention transformer | network (GATN) model to similar topology structures by

关键词： Radiofrequency identification | Topology | Network topology | Three-dimensional displays | Transformers | Optimization | Position measurement | Electromagnetics | Convolutional neural networks | Antennas...

摘要： Edge Graph Attention Neural Network (EGAT) model | accuracy and robustness of grid topology detection after | © 2024 Elsevier B.V.Against the backdrop of | growing power demand and market liberalization | , operators optimize power transmission and system load

关键词： Edge graph attention | Feature aggregation | Grid reconfiguration | Neural network | Topology detection

摘要：Topology Bench is a comprehensive topology | . Topology Bench addresses this limitation, offering a | network topologies through the lens of graph-theoretical | approach to topology selection. A statistical and | of these graph metrics and the relationships

关键词： Topology | Network topology | Optical fiber networks | Benchmark testing | Resource management | Measurement | Synthetic data | Optical imaging | Data models | Systematics

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国家科技图书文献中心

摘要： maximize modularity within a fixed graph topology | guide the enhancement of both graph* topology and* | outperforms state-of-the-art graph* construction methods in* | to a hundredfold increase in graph* construction* | Current modularity-based community detection

摘要： understanding and analyzing how graph* topology influences the* | influence of graph* topology by measuring the level of* | Graph neural networks (GNN) have achieved | features combined with topology* to create effective* | compatibility between the topological information of graph

摘要： with a graph. When only one feature per sensor is | causal graph. The first contribution extends VAR models | to matrix-variate models for the purpose of graph | of the graph* and trend from streaming samples* | The focus is on the statistical analysis of

摘要：Brain graph* super-resolution is an under* | leverage graph* neural networks (GNNs) thanks to their* | ability to natively handle graph-structured datasets | . However, numerous studies have shown that brain graph | topology is crucial in identifying the onset and presence

摘要： graph U-Net with topology-feature awareness pooling | pooled graph, the graphs topology* structure and node* | Nowadays, various graph* convolutional networks* | (GCNs) to process graph-structured data have been | emphasize graph node feature aggregation instead of graph

摘要： there is no systematic theory on topology* derivation* | of them. Therefore, a general topology* derivation* | based on graph* theory is proposed. The common-ground* | Common-ground transformerless single-phase | inverters are widely used in the photovoltaic generation

摘要： synergistic topology graph construction strategy using graph | topology graph construction (STGC) strategy makes up for | positions. After that, addressing the complex topology | the insensitivity of graph* attention transformer* | network (GATN) model to similar topology* structures by*

摘要： Edge Graph* Attention Neural Network (EGAT) model* | accuracy and robustness of grid topology* detection after* | © 2024 Elsevier B.V.Against the backdrop of | growing power demand and market liberalization | , operators optimize power transmission and system load

摘要：Topology Bench is a comprehensive topology | . Topology* Bench addresses this limitation, offering a* | network topologies through the lens of graph-theoretical | approach to topology* selection. A statistical and* | of these graph* metrics and the relationships*