# Graph Theory and Algorithms

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/graph-theory-and-algorithms/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on graph matching, graph processing, and pattern recognition techniques using distributed computing and parallel algorithms. It covers topics such as subgraph isomorphism, large-scale graphs, graph analytics, and spectral techniques for graph analysis. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t12292 |
| Works | 13 |

## Topic papers all

- [Graph neural networks: A review of methods and applications](https://scholariq.org/papers/graph-neural-networks-a-review-of-methods-and-applications-2/)
- [Graph Neural Networks: A Review of Methods and Applications](https://scholariq.org/papers/graph-neural-networks-a-review-of-methods-and-applications/)
- [A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions](https://scholariq.org/papers/a-review-of-graph-neural-networks-concepts-architectures-techniques-challenges/)
- [Factorized graph matching](https://scholariq.org/papers/factorized-graph-matching/)
- [GraphP: Reducing Communication for PIM-Based Graph Processing with Efficient Data Partition](https://scholariq.org/papers/graphp-reducing-communication-for-pim-based-graph-processing-with-efficient-data/)
- [Complex graph convolutional network for link prediction in knowledge graphs](https://scholariq.org/papers/complex-graph-convolutional-network-for-link-prediction-in-knowledge-graphs/)
- [<title>Maximum-weight bipartite matching technique and its application in image feature matching</title>](https://scholariq.org/papers/and-lt-title-and-gt-maximum-weight-bipartite-matching-technique-and-its/)
- [Inner sphere trees for proximity and penetration queries](https://scholariq.org/papers/inner-sphere-trees-for-proximity-and-penetration-queries/)
- [DHyper: A Recurrent Dual Hypergraph Neural Network for Event Prediction in Temporal Knowledge Graphs](https://scholariq.org/papers/dhyper-a-recurrent-dual-hypergraph-neural-network-for-event-prediction-in/)
- [Interactive and Intelligent Root Cause Analysis in Manufacturing with Causal Bayesian Networks and Knowledge Graphs](https://scholariq.org/papers/interactive-and-intelligent-root-cause-analysis-in-manufacturing-with-causal/)
- [Knowledge Graph Essentials and Key Technologies](https://scholariq.org/papers/knowledge-graph-essentials-and-key-technologies/)
- [Reliable Route Selection for Wireless Sensor Networks with Connection Failure Uncertainties](https://scholariq.org/papers/reliable-route-selection-for-wireless-sensor-networks-with-connection-failure/)
- [Knowledge-Enhanced Industrial Fault Detection via FMEA Graph Learning and Cross-Modal Feature Alignment](https://scholariq.org/papers/knowledge-enhanced-industrial-fault-detection-via-fmea-graph-learning-and-cross/)

## Topic primary papers

- [Factorized graph matching](https://scholariq.org/papers/factorized-graph-matching/)
- [GraphP: Reducing Communication for PIM-Based Graph Processing with Efficient Data Partition](https://scholariq.org/papers/graphp-reducing-communication-for-pim-based-graph-processing-with-efficient-data/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.