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Quantum kernels for unattributed graphs using discrete-time quantum walks

  • Published:2017-02 Issue: Volume:87 Page:96-103
  • ISSN:0167-8655
  • Container-title:Pattern Recognition Letters
  • language:en
  • Short-container-title:Pattern Recognition Letters

Author:

Bai LuORCID,Rossi LucaORCID,Cui Lixin,Zhang Zhihong,Ren Peng,Bai Xiao,Hancock EdwinORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference40 articles.

1. Backtrackless walks on a graph;Aziz;IEEE Trans. Neural Netw. Learn. Syst.,2013

2. Graph kernels between point clouds;Bach,2008

3. Graph kernels from the jensen-shannon divergence;Bai;J. Math. Imag. Vis.,2013

4. Fast depth-based subgraph kernels for unattributed graphs;Bai;Pattern Recogn.,2016

5. A hypergraph kernel from isomorphism tests;Bai,2014

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2. Graph kernels based on linear patterns: Theoretical and experimental comparisons;Expert Systems with Applications;2022-03

3. An R-Convolution Graph Kernel Based on Fast Discrete-Time Quantum Walk;IEEE Transactions on Neural Networks and Learning Systems;2022-01

4. Bosonic Random Walk Neural Networks for Graph Learning;Complex Networks & Their Applications X;2022

5. Fused lasso for feature selection using structural information;Pattern Recognition;2021-11
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