Deep belief network (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Deep belief network" in English language version.

refsWebsite

Global rank English rank

10doi.org

2^nd place

7nih.gov

4^th place

5psu.edu

207^th place

136^th place

5semanticscholar.org

11^th place

8^th place

2harvard.edu

18^th place

17^th place

2toronto.edu

low place

8,821^st place

2web.archive.org

1^st place

1nips.cc

low place

7,050^th place

1umontreal.ca

6,223^rd place

6,135^th place

1researchgate.net

120^th place

125^th place

1diku.dk

low place

1sanghv.com

low place

diku.dk

image.diku.dk

Fischer A, Igel C (2014). "Training Restricted Boltzmann Machines: An Introduction" (PDF). Pattern Recognition. 47 (1): 25–39. Bibcode:2014PatRe..47...25F. CiteSeerX 10.1.1.716.8647. doi:10.1016/j.patcog.2013.05.025. Archived from the original (PDF) on 2015-06-10. Retrieved 2017-07-02.

doi.org

Hinton G (2009). "Deep belief networks". Scholarpedia. 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947.
Hinton GE, Osindero S, Teh YW (July 2006). "A fast learning algorithm for deep belief nets" (PDF). Neural Computation. 18 (7): 1527–54. CiteSeerX 10.1.1.76.1541. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950.
Bengio, Y. (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2: 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006.
Movahedi F, Coyle JL, Sejdic E (May 2018). "Deep Belief Networks for Electroencephalography: A Review of Recent Contributions and Future Outlooks". IEEE Journal of Biomedical and Health Informatics. 22 (3): 642–652. doi:10.1109/jbhi.2017.2727218. PMC 5967386. PMID 28715343.
Ghasemi, Pérez-Sánchez; Mehri, Pérez-Garrido (2018). "Neural network and deep-learning algorithms used in QSAR studies: merits and drawbacks". Drug Discovery Today. 23 (10): 1784–1790. doi:10.1016/j.drudis.2018.06.016. PMID 29936244. S2CID 49418479.
Ghasemi, Pérez-Sánchez; Mehri, fassihi (2016). "The Role of Different Sampling Methods in Improving Biological Activity Prediction Using Deep Belief Network". Journal of Computational Chemistry. 38 (10): 1–8. doi:10.1002/jcc.24671. PMID 27862046. S2CID 12077015.
Gawehn E, Hiss JA, Schneider G (January 2016). "Deep Learning in Drug Discovery". Molecular Informatics. 35 (1): 3–14. doi:10.1002/minf.201501008. PMID 27491648. S2CID 10574953.
Hinton GE (2002). "Training Product of Experts by Minimizing Contrastive Divergence" (PDF). Neural Computation. 14 (8): 1771–1800. CiteSeerX 10.1.1.35.8613. doi:10.1162/089976602760128018. PMID 12180402. S2CID 207596505.
Fischer A, Igel C (2014). "Training Restricted Boltzmann Machines: An Introduction" (PDF). Pattern Recognition. 47 (1): 25–39. Bibcode:2014PatRe..47...25F. CiteSeerX 10.1.1.716.8647. doi:10.1016/j.patcog.2013.05.025. Archived from the original (PDF) on 2015-06-10. Retrieved 2017-07-02.
Bengio Y (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. Archived from the original (PDF) on 2016-03-04. Retrieved 2017-07-02.

harvard.edu

ui.adsabs.harvard.edu

Hinton G (2009). "Deep belief networks". Scholarpedia. 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947.
Fischer A, Igel C (2014). "Training Restricted Boltzmann Machines: An Introduction" (PDF). Pattern Recognition. 47 (1): 25–39. Bibcode:2014PatRe..47...25F. CiteSeerX 10.1.1.716.8647. doi:10.1016/j.patcog.2013.05.025. Archived from the original (PDF) on 2015-06-10. Retrieved 2017-07-02.

nih.gov

pubmed.ncbi.nlm.nih.gov

Hinton GE, Osindero S, Teh YW (July 2006). "A fast learning algorithm for deep belief nets" (PDF). Neural Computation. 18 (7): 1527–54. CiteSeerX 10.1.1.76.1541. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950.
Movahedi F, Coyle JL, Sejdic E (May 2018). "Deep Belief Networks for Electroencephalography: A Review of Recent Contributions and Future Outlooks". IEEE Journal of Biomedical and Health Informatics. 22 (3): 642–652. doi:10.1109/jbhi.2017.2727218. PMC 5967386. PMID 28715343.
Ghasemi, Pérez-Sánchez; Mehri, Pérez-Garrido (2018). "Neural network and deep-learning algorithms used in QSAR studies: merits and drawbacks". Drug Discovery Today. 23 (10): 1784–1790. doi:10.1016/j.drudis.2018.06.016. PMID 29936244. S2CID 49418479.
Ghasemi, Pérez-Sánchez; Mehri, fassihi (2016). "The Role of Different Sampling Methods in Improving Biological Activity Prediction Using Deep Belief Network". Journal of Computational Chemistry. 38 (10): 1–8. doi:10.1002/jcc.24671. PMID 27862046. S2CID 12077015.
Gawehn E, Hiss JA, Schneider G (January 2016). "Deep Learning in Drug Discovery". Molecular Informatics. 35 (1): 3–14. doi:10.1002/minf.201501008. PMID 27491648. S2CID 10574953.
Hinton GE (2002). "Training Product of Experts by Minimizing Contrastive Divergence" (PDF). Neural Computation. 14 (8): 1771–1800. CiteSeerX 10.1.1.35.8613. doi:10.1162/089976602760128018. PMID 12180402. S2CID 207596505.

ncbi.nlm.nih.gov

Movahedi F, Coyle JL, Sejdic E (May 2018). "Deep Belief Networks for Electroencephalography: A Review of Recent Contributions and Future Outlooks". IEEE Journal of Biomedical and Health Informatics. 22 (3): 642–652. doi:10.1109/jbhi.2017.2727218. PMC 5967386. PMID 28715343.

nips.cc

papers.nips.cc

Bengio Y, Lamblin P, Popovici D, Larochelle H (2007). Greedy Layer-Wise Training of Deep Networks (PDF). NIPS.

psu.edu

citeseerx.ist.psu.edu

Hinton GE, Osindero S, Teh YW (July 2006). "A fast learning algorithm for deep belief nets" (PDF). Neural Computation. 18 (7): 1527–54. CiteSeerX 10.1.1.76.1541. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950.
Bengio, Y. (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2: 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006.
Hinton GE (2002). "Training Product of Experts by Minimizing Contrastive Divergence" (PDF). Neural Computation. 14 (8): 1771–1800. CiteSeerX 10.1.1.35.8613. doi:10.1162/089976602760128018. PMID 12180402. S2CID 207596505.
Fischer A, Igel C (2014). "Training Restricted Boltzmann Machines: An Introduction" (PDF). Pattern Recognition. 47 (1): 25–39. Bibcode:2014PatRe..47...25F. CiteSeerX 10.1.1.716.8647. doi:10.1016/j.patcog.2013.05.025. Archived from the original (PDF) on 2015-06-10. Retrieved 2017-07-02.
Bengio Y (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. Archived from the original (PDF) on 2016-03-04. Retrieved 2017-07-02.

researchgate.net

Hinton GE (2010). "A Practical Guide to Training Restricted Boltzmann Machines". Tech. Rep. UTML TR 2010-003.

sanghv.com

Bengio Y (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. Archived from the original (PDF) on 2016-03-04. Retrieved 2017-07-02.

semanticscholar.org

api.semanticscholar.org

Hinton GE, Osindero S, Teh YW (July 2006). "A fast learning algorithm for deep belief nets" (PDF). Neural Computation. 18 (7): 1527–54. CiteSeerX 10.1.1.76.1541. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950.
Ghasemi, Pérez-Sánchez; Mehri, Pérez-Garrido (2018). "Neural network and deep-learning algorithms used in QSAR studies: merits and drawbacks". Drug Discovery Today. 23 (10): 1784–1790. doi:10.1016/j.drudis.2018.06.016. PMID 29936244. S2CID 49418479.
Ghasemi, Pérez-Sánchez; Mehri, fassihi (2016). "The Role of Different Sampling Methods in Improving Biological Activity Prediction Using Deep Belief Network". Journal of Computational Chemistry. 38 (10): 1–8. doi:10.1002/jcc.24671. PMID 27862046. S2CID 12077015.
Gawehn E, Hiss JA, Schneider G (January 2016). "Deep Learning in Drug Discovery". Molecular Informatics. 35 (1): 3–14. doi:10.1002/minf.201501008. PMID 27491648. S2CID 10574953.
Hinton GE (2002). "Training Product of Experts by Minimizing Contrastive Divergence" (PDF). Neural Computation. 14 (8): 1771–1800. CiteSeerX 10.1.1.35.8613. doi:10.1162/089976602760128018. PMID 12180402. S2CID 207596505.

toronto.edu

cs.toronto.edu

Hinton GE, Osindero S, Teh YW (July 2006). "A fast learning algorithm for deep belief nets" (PDF). Neural Computation. 18 (7): 1527–54. CiteSeerX 10.1.1.76.1541. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950.
Hinton GE (2002). "Training Product of Experts by Minimizing Contrastive Divergence" (PDF). Neural Computation. 14 (8): 1771–1800. CiteSeerX 10.1.1.35.8613. doi:10.1162/089976602760128018. PMID 12180402. S2CID 207596505.

umontreal.ca

iro.umontreal.ca

Bengio, Y. (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2: 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006.

web.archive.org

Fischer A, Igel C (2014). "Training Restricted Boltzmann Machines: An Introduction" (PDF). Pattern Recognition. 47 (1): 25–39. Bibcode:2014PatRe..47...25F. CiteSeerX 10.1.1.716.8647. doi:10.1016/j.patcog.2013.05.025. Archived from the original (PDF) on 2015-06-10. Retrieved 2017-07-02.
Bengio Y (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. Archived from the original (PDF) on 2016-03-04. Retrieved 2017-07-02.