심층 신뢰 신경망 (Korean Wikipedia)

Analysis of information sources in references of the Wikipedia article "심층 신뢰 신경망" in Korean language version.

refsWebsite

Global rank Korean rank

7doi.org

2^nd place

3^rd place

5nih.gov

4^th place

4semanticscholar.org

11^th place

310^th place

2psu.edu

207^th place

220^th place

1harvard.edu

18^th place

27^th place

1toronto.edu

low place

7,296^th place

1nips.cc

low place

5,015^th place

1umontreal.ca

6,223^rd place

3,156^th place

doi.org

dx.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》 (미국 영어) 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.

harvard.edu

adsabs.harvard.edu

Hinton G (2009). “Deep belief networks”. 《Scholarpedia》 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947.

nih.gov

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》 (미국 영어) 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.

nips.cc

papers.nips.cc

Bengio, Yoshua; Lamblin, Pascal; Popovici, Dan; Larochelle, Hugh (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.

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.

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.

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.