Învățare profundă (Romanian Wikipedia)
Analysis of information sources in references of the Wikipedia article "Învățare profundă" in Romanian language version.
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acm.org
dl.acm.org
- Bengio, Yoshua; Ducharme, Réjean; Vincent, Pascal; Janvin, Christian (martie 2003). „A Neural Probabilistic Language Model”. J. Mach. Learn. Res. 3: 1137–1155. ISSN 1532-4435.
arxiv.org
- Un robot va completa această citare în curând. Clic aici pentru a trece mai în față arXiv:[1].
datascienceassn.org
- „Multi-task Neural Networks for QSAR Predictions | Data Science Association”. www.datascienceassn.org. Accesat în .
doi.org
- Bengio, Y.; Courville, A.; Vincent, P. (). „Representation Learning: A Review and New Perspectives”. IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. doi:10.1109/tpami.2013.50. PMID 23787338.
- Schmidhuber, J. (). „Deep Learning in Neural Networks: An Overview”. Neural Networks. 61: 85–117. doi:10.1016/j.neunet.2014.09.003. PMID 25462637.
- Bengio, Yoshua; LeCun, Yann; Hinton, Geoffrey (). „Deep Learning”. Nature. 521 (7553): 436–444. Bibcode:2015Natur.521..436L. doi:10.1038/nature14539. PMID 26017442.
- Ciresan, Dan; Meier, U.; Schmidhuber, J. (iunie 2012). „Multi-column deep neural networks for image classification”. 2012 IEEE Conference on Computer Vision and Pattern Recognition: 3642–3649. doi:10.1109/cvpr.2012.6248110. ISBN 978-1-4673-1228-8.
- Marblestone, Adam H.; Wayne, Greg; Kording, Konrad P. (). „Toward an Integration of Deep Learning and Neuroscience”. Frontiers in Computational Neuroscience. 10: 94. doi:10.3389/fncom.2016.00094. PMC 5021692
. PMID 27683554. - Olshausen, B. A. (). „Emergence of simple-cell receptive field properties by learning a sparse code for natural images”. Nature. 381 (6583): 607–609. Bibcode:1996Natur.381..607O. doi:10.1038/381607a0. PMID 8637596.
- Deng, L.; Yu, D. (). „Deep Learning: Methods and Applications” (PDF). Foundations and Trends in Signal Processing. 7 (3–4): 1–199. doi:10.1561/2000000039.
- Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda (ianuarie 2016). „Mastering the game of Go with deep neural networks and tree search”. Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 1476-4687. PMID 26819042.
- Bengio, Yoshua (). „Learning Deep Architectures for AI” (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. doi:10.1561/2200000006. Arhivat din original (PDF) la . Accesat în .
- Gers, Felix A.; Schmidhuber, Jürgen (). „LSTM Recurrent Networks Learn Simple Context Free and Context Sensitive Languages”. IEEE Trans. Neural Netw. 12 (6): 1333–1340. doi:10.1109/72.963769. PMID 18249962.
- Hochreiter, Sepp; Schmidhuber, Jürgen (). „Long Short-Term Memory”. Neural Computation. 9 (8): 1735–1780. doi:10.1162/neco.1997.9.8.1735. ISSN 0899-7667. PMID 9377276.
- LeCun, Y.; et al. (). „Gradient-based learning applied to document recognition”. Proceedings of the IEEE. 86 (11): 2278–2324. doi:10.1109/5.726791.
- Sainath, T. N.; Mohamed, A. r; Kingsbury, B.; Ramabhadran, B. (mai 2013). „Deep convolutional neural networks for LVCSR”. 2013 IEEE International Conference on Acoustics, Speech and Signal Processing: 8614–8618. doi:10.1109/icassp.2013.6639347. ISBN 978-1-4799-0356-6.
- Arrowsmith, J; Miller, P (). „Trial watch: Phase II and phase III attrition rates 2011-2012”. Nature Reviews Drug Discovery. 12 (8): 569. doi:10.1038/nrd4090. PMID 23903212.
- Verbist, B; Klambauer, G; Vervoort, L; Talloen, W; The Qstar, Consortium; Shkedy, Z; Thas, O; Bender, A; Göhlmann, H. W. (). „Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project”. Drug Discovery Today. 20 (5): 505–513. doi:10.1016/j.drudis.2014.12.014. PMID 25582842.
- Chicco, Davide; Sadowski, Peter; Baldi, Pierre (). Deep Autoencoder Neural Networks for Gene Ontology Annotation Predictions. Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14. ACM. pp. 533–540. doi:10.1145/2649387.2649442. ISBN 9781450328944.
- Sathyanarayana, Aarti (). „Sleep Quality Prediction From Wearable Data Using Deep Learning”. JMIR mHealth and uHealth. 4 (4): e125. doi:10.2196/mhealth.6562. PMC 5116102 . PMID 27815231.
- Choi, Edward; Schuetz, Andy; Stewart, Walter F.; Sun, Jimeng (). „Using recurrent neural network models for early detection of heart failure onset”. Journal of the American Medical Informatics Association. 24 (2): 361–370. doi:10.1093/jamia/ocw112. ISSN 1067-5027. PMC 5391725 . PMID 27521897.
- Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A.W.M.; van Ginneken, Bram; Sánchez, Clara I. (decembrie 2017). „A survey on deep learning in medical image analysis”. Medical Image Analysis. 42: 60–88. doi:10.1016/j.media.2017.07.005.
- Forslid, Gustav; Wieslander, Hakan; Bengtsson, Ewert; Wahlby, Carolina; Hirsch, Jan-Michael; Stark, Christina Runow; Sadanandan, Sajith Kecheril (octombrie 2017). „Deep Convolutional Neural Networks for Detecting Cellular Changes Due to Malignancy”. 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). Venice: IEEE: 82–89. doi:10.1109/ICCVW.2017.18. ISBN 9781538610343.
elsevier.com
linkinghub.elsevier.com
- Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A.W.M.; van Ginneken, Bram; Sánchez, Clara I. (decembrie 2017). „A survey on deep learning in medical image analysis”. Medical Image Analysis. 42: 60–88. doi:10.1016/j.media.2017.07.005.
g2.com
learn.g2.com
- Shah, Hardik. „A Full Overview of Artificial Neural Networks (ANN)” (în engleză). learn.g2.com. Accesat în .
globalbankingandfinance.com
- Czech, Tomasz. „Deep learning: the next frontier for money laundering detection”. Global Banking and Finance Review.
harvard.edu
adsabs.harvard.edu
- Bengio, Yoshua; LeCun, Yann; Hinton, Geoffrey (). „Deep Learning”. Nature. 521 (7553): 436–444. Bibcode:2015Natur.521..436L. doi:10.1038/nature14539. PMID 26017442.
- Olshausen, B. A. (). „Emergence of simple-cell receptive field properties by learning a sparse code for natural images”. Nature. 381 (6583): 607–609. Bibcode:1996Natur.381..607O. doi:10.1038/381607a0. PMID 8637596.
- Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda (ianuarie 2016). „Mastering the game of Go with deep neural networks and tree search”. Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 1476-4687. PMID 26819042.
ieee.org
ieeexplore.ieee.org
- Ciresan, Dan; Meier, U.; Schmidhuber, J. (iunie 2012). „Multi-column deep neural networks for image classification”. 2012 IEEE Conference on Computer Vision and Pattern Recognition: 3642–3649. doi:10.1109/cvpr.2012.6248110. ISBN 978-1-4673-1228-8.
- Sainath, T. N.; Mohamed, A. r; Kingsbury, B.; Ramabhadran, B. (mai 2013). „Deep convolutional neural networks for LVCSR”. 2013 IEEE International Conference on Acoustics, Speech and Signal Processing: 8614–8618. doi:10.1109/icassp.2013.6639347. ISBN 978-1-4799-0356-6.
- Forslid, Gustav; Wieslander, Hakan; Bengtsson, Ewert; Wahlby, Carolina; Hirsch, Jan-Michael; Stark, Christina Runow; Sadanandan, Sajith Kecheril (octombrie 2017). „Deep Convolutional Neural Networks for Detecting Cellular Changes Due to Malignancy”. 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). Venice: IEEE: 82–89. doi:10.1109/ICCVW.2017.18. ISBN 9781538610343.
medium.com
- „Deep Learning in Healthcare: Challenges and Opportunities”. Medium. . Accesat în .
microsoft.com
research.microsoft.com
- Deng, L.; Yu, D. (). „Deep Learning: Methods and Applications” (PDF). Foundations and Trends in Signal Processing. 7 (3–4): 1–199. doi:10.1561/2000000039.
- „Plenary presentation at ICASSP-2016” (PDF).
nih.gov
ncbi.nlm.nih.gov
- Bengio, Y.; Courville, A.; Vincent, P. (). „Representation Learning: A Review and New Perspectives”. IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. doi:10.1109/tpami.2013.50. PMID 23787338.
- Schmidhuber, J. (). „Deep Learning in Neural Networks: An Overview”. Neural Networks. 61: 85–117. doi:10.1016/j.neunet.2014.09.003. PMID 25462637.
- Bengio, Yoshua; LeCun, Yann; Hinton, Geoffrey (). „Deep Learning”. Nature. 521 (7553): 436–444. Bibcode:2015Natur.521..436L. doi:10.1038/nature14539. PMID 26017442.
- Marblestone, Adam H.; Wayne, Greg; Kording, Konrad P. (). „Toward an Integration of Deep Learning and Neuroscience”. Frontiers in Computational Neuroscience. 10: 94. doi:10.3389/fncom.2016.00094. PMC 5021692 . PMID 27683554.
- Olshausen, B. A. (). „Emergence of simple-cell receptive field properties by learning a sparse code for natural images”. Nature. 381 (6583): 607–609. Bibcode:1996Natur.381..607O. doi:10.1038/381607a0. PMID 8637596.
- Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda (ianuarie 2016). „Mastering the game of Go with deep neural networks and tree search”. Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 1476-4687. PMID 26819042.
- Gers, Felix A.; Schmidhuber, Jürgen (). „LSTM Recurrent Networks Learn Simple Context Free and Context Sensitive Languages”. IEEE Trans. Neural Netw. 12 (6): 1333–1340. doi:10.1109/72.963769. PMID 18249962.
- Hochreiter, Sepp; Schmidhuber, Jürgen (). „Long Short-Term Memory”. Neural Computation. 9 (8): 1735–1780. doi:10.1162/neco.1997.9.8.1735. ISSN 0899-7667. PMID 9377276.
- Arrowsmith, J; Miller, P (). „Trial watch: Phase II and phase III attrition rates 2011-2012”. Nature Reviews Drug Discovery. 12 (8): 569. doi:10.1038/nrd4090. PMID 23903212.
- Verbist, B; Klambauer, G; Vervoort, L; Talloen, W; The Qstar, Consortium; Shkedy, Z; Thas, O; Bender, A; Göhlmann, H. W. (). „Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project”. Drug Discovery Today. 20 (5): 505–513. doi:10.1016/j.drudis.2014.12.014. PMID 25582842.
- Sathyanarayana, Aarti (). „Sleep Quality Prediction From Wearable Data Using Deep Learning”. JMIR mHealth and uHealth. 4 (4): e125. doi:10.2196/mhealth.6562. PMC 5116102 . PMID 27815231.
- Choi, Edward; Schuetz, Andy; Stewart, Walter F.; Sun, Jimeng (). „Using recurrent neural network models for early detection of heart failure onset”. Journal of the American Medical Informatics Association. 24 (2): 361–370. doi:10.1093/jamia/ocw112. ISSN 1067-5027. PMC 5391725 . PMID 27521897.
tripod.nih.gov
ncats.nih.gov
- „Archived copy”. Arhivat din original la . Accesat în .
nips.cc
papers.nips.cc
- Szegedy, Christian; Toshev, Alexander; Erhan, Dumitru (). „Deep neural networks for object detection”. Advances in Neural Information Processing Systems.
- Sutskever, L.; Vinyals, O.; Le, Q. (). „Sequence to Sequence Learning with Neural Networks” (PDF). Proc. NIPS.
oxfordjournals.org
jamia.oxfordjournals.org
- Choi, Edward; Schuetz, Andy; Stewart, Walter F.; Sun, Jimeng (). „Using recurrent neural network models for early detection of heart failure onset”. Journal of the American Medical Informatics Association. 24 (2): 361–370. doi:10.1093/jamia/ocw112. ISSN 1067-5027. PMC 5391725 . PMID 27521897.
researchgate.net
- Rina Dechter (1986). Learning while searching in constraint-satisfaction problems. University of California, Computer Science Department, Cognitive Systems Laboratory.Online
- „Learning Precise Timing with LSTM Recurrent Networks (PDF Download Available)”. ResearchGate. Accesat în .
sanghv.com
- Bengio, Yoshua (). „Learning Deep Architectures for AI” (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. doi:10.1561/2200000006. Arhivat din original (PDF) la . Accesat în .
scholarpedia.org
- Jürgen Schmidhuber (2015). Deep Learning. Scholarpedia, 10(11):32832. Online
techcrunch.com
tools.wmflabs.org
- Un robot va completa această citare în curând. Clic aici pentru a trece mai în față arXiv:[1].
toronto.edu
cs.toronto.edu
- Krizhevsky, Alex; Sutskever, Ilya; Hinton, Geoffry (). „ImageNet Classification with Deep Convolutional Neural Networks” (PDF). NIPS 2012: Neural Information Processing Systems, Lake Tahoe, Nevada.
vutbr.cz
fit.vutbr.cz
- Mikolov, T.; et al. (). „Recurrent neural network based language model” (PDF). Interspeech. Arhivat din original (PDF) la . Accesat în .
web.archive.org
- Bengio, Yoshua (). „Learning Deep Architectures for AI” (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. doi:10.1561/2200000006. Arhivat din original (PDF) la . Accesat în .
- Mikolov, T.; et al. (). „Recurrent neural network based language model” (PDF). Interspeech. Arhivat din original (PDF) la . Accesat în .
- Graves, Alex; Eck, Douglas; Beringer, Nicole; Schmidhuber, Jürgen (). „Biologically Plausible Speech Recognition with LSTM Neural Nets” (PDF). 1st Intl. Workshop on Biologically Inspired Approaches to Advanced Information Technology, Bio-ADIT 2004, Lausanne, Switzerland. pp. 175–184. Arhivat din original (PDF) la .
- „Archived copy”. Arhivat din original la . Accesat în .
wired.com
- „How Skype Used AI to Build Its Amazing New Language Translator | WIRED”. www.wired.com. Accesat în .
worldcat.org
- Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda (ianuarie 2016). „Mastering the game of Go with deep neural networks and tree search”. Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 1476-4687. PMID 26819042.
- Hochreiter, Sepp; Schmidhuber, Jürgen (). „Long Short-Term Memory”. Neural Computation. 9 (8): 1735–1780. doi:10.1162/neco.1997.9.8.1735. ISSN 0899-7667. PMID 9377276.
- Bengio, Yoshua; Ducharme, Réjean; Vincent, Pascal; Janvin, Christian (martie 2003). „A Neural Probabilistic Language Model”. J. Mach. Learn. Res. 3: 1137–1155. ISSN 1532-4435.
- Choi, Edward; Schuetz, Andy; Stewart, Walter F.; Sun, Jimeng (). „Using recurrent neural network models for early detection of heart failure onset”. Journal of the American Medical Informatics Association. 24 (2): 361–370. doi:10.1093/jamia/ocw112. ISSN 1067-5027. PMC 5391725 . PMID 27521897.