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Path Matching and Graph Matching in Biological Networks

Journal of Computational Biology, 2007
We develop algorithms for the following path matching and graph matching problems: (i) given a query path p and a graph G, find a path p' that is most similar to p in G; (ii) given a query graph G (0) and a graph G, find a graph G (0)' that is most similar to G (0) in G.
Sing-Hoi Sze
exaly   +3 more sources

Determination of the Impedance Matching Domain of Impedance Matching Networks

IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2004
This paper investigates the impedance boundary of impedance matching networks analytically, graphically representing the resultant impedance matching domains. A set of explicit equations is derived to allow the rapid development of the impedance boundary of such networks.
Michael Thompson, J K Fidler
exaly   +2 more sources

Matching Networks

Wireless Communication Electronics, 2012
R. Sobot
openaire   +2 more sources

Matching Networks

Elements of Radio Frequency Energy Harvesting and Wireless Power Transfer Systems, 2020
Taimoor Khan Nasimuddin   +1 more
openaire   +2 more sources

H2MN: Graph Similarity Learning with Hierarchical Hypergraph Matching Networks

Knowledge Discovery and Data Mining, 2021
Graph similarity learning, which measures the similarities between a pair of graph-structured objects, lies at the core of various machine learning tasks such as graph classification, similarity search, etc.
Zhen Zhang   +6 more
semanticscholar   +1 more source

Proxy Graph Matching with Proximal Matching Networks

Proceedings of the AAAI Conference on Artificial Intelligence, 2021
Estimating feature point correspondence is a common technique in computer vision. A line of recent data-driven approaches utilizing the graph neural networks improved the matching accuracy by a large margin. However, these learning-based methods require a lot of labeled training data, which are expensive to collect.
Haoru Tan   +5 more
openaire   +1 more source

TMN: Trajectory Matching Networks for Predicting Similarity

IEEE International Conference on Data Engineering, 2022
Trajectory similarity computation is the cornerstone of many applications in the field of trajectory data analysis. To cope with the high time complexity of calculating exact similarity between trajectories, learning-based models have been developed for ...
Peilun Yang   +5 more
semanticscholar   +1 more source

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