These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
325 related articles for article (PubMed ID: 19814905)
1. Novel kernels for error-tolerant graph classification. Neuhaus M; Riesen K; Bunke H Spat Vis; 2009; 22(5):425-41. PubMed ID: 19814905 [TBL] [Abstract][Full Text] [Related]
2. Graph kernels for molecular structure-activity relationship analysis with support vector machines. Mahé P; Ueda N; Akutsu T; Perret JL; Vert JP J Chem Inf Model; 2005; 45(4):939-51. PubMed ID: 16045288 [TBL] [Abstract][Full Text] [Related]
3. An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification. Fouss F; Francoisse K; Yen L; Pirotte A; Saerens M Neural Netw; 2012 Jul; 31():53-72. PubMed ID: 22497802 [TBL] [Abstract][Full Text] [Related]
4. Graph classification by means of Lipschitz embedding. Riesen K; Bunke H IEEE Trans Syst Man Cybern B Cybern; 2009 Dec; 39(6):1472-83. PubMed ID: 19447721 [TBL] [Abstract][Full Text] [Related]
5. Kernel discriminant analysis for positive definite and indefinite kernels. Pekalska E; Haasdonk B IEEE Trans Pattern Anal Mach Intell; 2009 Jun; 31(6):1017-32. PubMed ID: 19372607 [TBL] [Abstract][Full Text] [Related]
6. A novel kernel-based maximum a posteriori classification method. Xu Z; Huang K; Zhu J; King I; Lyu MR Neural Netw; 2009 Sep; 22(7):977-87. PubMed ID: 19167865 [TBL] [Abstract][Full Text] [Related]
7. Context-dependent kernels for object classification. Sahbi H; Audibert JY; Keriven R IEEE Trans Pattern Anal Mach Intell; 2011 Apr; 33(4):699-708. PubMed ID: 21079276 [TBL] [Abstract][Full Text] [Related]
8. Graph kernels for chemical informatics. Ralaivola L; Swamidass SJ; Saigo H; Baldi P Neural Netw; 2005 Oct; 18(8):1093-110. PubMed ID: 16157471 [TBL] [Abstract][Full Text] [Related]
10. Context-Dependent Random Walk Graph Kernels and Tree Pattern Graph Matching Kernels with Applications to Action Recognition. Hu W; Wu B; Wang P; Yuan C; Li Y; Maybank S IEEE Trans Image Process; 2018 Jun; ():. PubMed ID: 29994476 [TBL] [Abstract][Full Text] [Related]
11. Training similarity measures for specific activities: application to reduced graphs. Birchall K; Gillet VJ; Harper G; Pickett SD J Chem Inf Model; 2006; 46(2):577-86. PubMed ID: 16562986 [TBL] [Abstract][Full Text] [Related]
12. Graph kernels combined with the neural network on protein classification. Qiangrong J; Guang Q J Bioinform Comput Biol; 2019 Oct; 17(5):1950030. PubMed ID: 31856667 [TBL] [Abstract][Full Text] [Related]
13. Atom environment kernels on molecules. Yamashita H; Higuchi T; Yoshida R J Chem Inf Model; 2014 May; 54(5):1289-300. PubMed ID: 24802375 [TBL] [Abstract][Full Text] [Related]
14. Combining feature- and correspondence-based methods for visual object recognition. Westphal G; Würtz RP Neural Comput; 2009 Jul; 21(7):1952-89. PubMed ID: 19292649 [TBL] [Abstract][Full Text] [Related]
15. Minimum classification error-based weighted support vector machine kernels for speaker verification. Suh Y; Kim H J Acoust Soc Am; 2013 Apr; 133(4):EL307-13. PubMed ID: 23556696 [TBL] [Abstract][Full Text] [Related]
16. Nonlinear support vector machine visualization for risk factor analysis using nomograms and localized radial basis function kernels. Cho BH; Yu H; Lee J; Chee YJ; Kim IY; Kim SI IEEE Trans Inf Technol Biomed; 2008 Mar; 12(2):247-56. PubMed ID: 18348954 [TBL] [Abstract][Full Text] [Related]
17. A novel graph kernel on chemical compound classification. Jiang Q; Ma J J Bioinform Comput Biol; 2018 Dec; 16(6):1850026. PubMed ID: 30567474 [TBL] [Abstract][Full Text] [Related]
18. A Comprehensive Evaluation of Graph Kernels for Unattributed Graphs. Zhang Y; Wang L; Wang L Entropy (Basel); 2018 Dec; 20(12):. PubMed ID: 33266707 [TBL] [Abstract][Full Text] [Related]
19. Graph wavelet alignment kernels for drug virtual screening. Smalter A; Huan J; Lushington G Comput Syst Bioinformatics Conf; 2008; 7():327-38. PubMed ID: 19642292 [TBL] [Abstract][Full Text] [Related]
20. Ligand prediction for orphan targets using support vector machines and various target-ligand kernels is dominated by nearest neighbor effects. Wassermann AM; Geppert H; Bajorath J J Chem Inf Model; 2009 Oct; 49(10):2155-67. PubMed ID: 19780576 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]