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Sparse Graph and dense Graph
Sparse Multi-Relational Graph Convolutional Network for Multi-type Object Trajectory Prediction
Graphons are graph limits, and can be used to generate new graphs with desired properties. Intuitive...
The Floyd Warshall algorithm is for solving the All Pairs Shortest Path problem. The problem is to...
Recent trends in NLP utilize knowledge graphs (KGs) to enhance pretrained language models by incorpo...
🧮 Space Matrix in Data Structures A space matrix (or sparse matrix) is a type of matrix that has...
Kruskal's Algorithm is a greedy algorithm used to find the Minimum Spanning Tree (MST) of a conn...
This is a short summary of what graphs are, the types of graphs and how they are implemented. Some...
a detailed presentation on graphs in data structure
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Graph Neural Networks for End-to-End Information Extraction from Handwritten Documents
Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local Graph
Self-supervised Graph Learning for Recommendation
Graph Representation Learning Meets Computer Vision: A Survey
Scalable Spatiotemporal Graph Neural Networks
Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction
Graph Theory-The Foundations of Modern Networks
A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspec...
Combinatorial Optimization
SeedGNN: Graph Neural Network for Supervised Seeded Graph Matching
A Generalization of Transformer Networks to Graphs
It is Data-Structure