Autoencoder (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Autoencoder" in English language version.

refsWebsite

Global rank English rank

34doi.org

2^nd place

17semanticscholar.org

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16arxiv.org

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12nih.gov

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8harvard.edu

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8worldcat.org

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4acm.org

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3neurips.cc

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2springer.com

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2sciencedirect.com

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2handle.net

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1deeplearningbook.org

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1toronto.edu

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1ntu.edu.tw

2,798^th place

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1researchgate.net

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1umontreal.ca

6,223^rd place

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1psu.edu

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1stanford.edu

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1mit.edu

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1aip.org

2,204^th place

1,735^th place

1escholarship.org

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1epfl.ch

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1torch.ch

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1wiley.com

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1github.com

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1ieee.org

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1snu.ac.kr

low place

1archives-ouvertes.fr

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1wired.com

193^rd place

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acm.org

dl.acm.org

Nair, Vinod; Hinton, Geoffrey E. (2009). "3D Object Recognition with Deep Belief Nets". Proceedings of the 22nd International Conference on Neural Information Processing Systems. NIPS'09. USA: Curran Associates Inc.: 1339–1347. ISBN 9781615679119.
Chicco, Davide; Sadowski, Peter; Baldi, Pierre (2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14. p. 533. doi:10.1145/2649387.2649442. hdl:11311/964622. ISBN 9781450328944. S2CID 207217210.
Sakurada, Mayu; Yairi, Takehisa (December 2014). "Anomaly Detection Using Autoencoders with Nonlinear Dimensionality Reduction". Proceedings of the MLSDA 2014 2nd Workshop on Machine Learning for Sensory Data Analysis. Gold Coast, Australia QLD, Australia: ACM Press. pp. 4–11. doi:10.1145/2689746.2689747. ISBN 978-1-4503-3159-3. S2CID 14613395.
Zhou, Chong; Paffenroth, Randy C. (2017-08-04). "Anomaly Detection with Robust Deep Autoencoders". Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM. pp. 665–674. doi:10.1145/3097983.3098052. ISBN 978-1-4503-4887-4. S2CID 207557733.

aip.org

pubs.aip.org

Elman, Jeffrey L.; Zipser, David (1988-04-01). "Learning the hidden structure of speech". The Journal of the Acoustical Society of America. 83 (4): 1615–1626. Bibcode:1988ASAJ...83.1615E. doi:10.1121/1.395916. ISSN 0001-4966. PMID 3372872.

archives-ouvertes.fr

hal.archives-ouvertes.fr

Buades, A.; Coll, B.; Morel, J. M. (2005). "A Review of Image Denoising Algorithms, with a New One". Multiscale Modeling & Simulation. 4 (2): 490–530. doi:10.1137/040616024. S2CID 218466166.

arxiv.org

Welling, Max; Kingma, Diederik P. (2019). "An Introduction to Variational Autoencoders". Foundations and Trends in Machine Learning. 12 (4): 307–392. arXiv:1906.02691. Bibcode:2019arXiv190602691K. doi:10.1561/2200000056. S2CID 174802445.
Makhzani, Alireza; Frey, Brendan (2013). "K-Sparse Autoencoders". arXiv:1312.5663 [cs.LG].
Abid, Abubakar; Balin, Muhammad Fatih; Zou, James (2019-01-27). "Concrete Autoencoders for Differentiable Feature Selection and Reconstruction". arXiv:1901.09346 [cs.LG].
Zhou, Yingbo; Arpit, Devansh; Nwogu, Ifeoma; Govindaraju, Venu (2014). "Is Joint Training Better for Deep Auto-Encoders?". arXiv:1405.1380 [stat.ML].
Schmidhuber, Jürgen (January 2015). "Deep learning in neural networks: An overview". Neural Networks. 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003. PMID 25462637. S2CID 11715509.
Diederik P Kingma; Welling, Max (2013). "Auto-Encoding Variational Bayes". arXiv:1312.6114 [stat.ML].
Plaut, E (2018). "From Principal Subspaces to Principal Components with Linear Autoencoders". arXiv:1804.10253 [stat.ML].
Nalisnick, Eric; Matsukawa, Akihiro; Teh, Yee Whye; Gorur, Dilan; Lakshminarayanan, Balaji (2019-02-24). "Do Deep Generative Models Know What They Don't Know?". arXiv:1810.09136 [stat.ML].
Xiao, Zhisheng; Yan, Qing; Amit, Yali (2020). "Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder". Advances in Neural Information Processing Systems. 33. arXiv:2003.02977.
Theis, Lucas; Shi, Wenzhe; Cunningham, Andrew; Huszár, Ferenc (2017). "Lossy Image Compression with Compressive Autoencoders". arXiv:1703.00395 [stat.ML].
Balle, J; Laparra, V; Simoncelli, EP (April 2017). "End-to-end optimized image compression". International Conference on Learning Representations. arXiv:1611.01704.
Cho, Kyunghyun (2013). "Boltzmann Machines and Denoising Autoencoders for Image Denoising". arXiv:1301.3468 [stat.ML].
Gondara, Lovedeep (December 2016). "Medical Image Denoising Using Convolutional Denoising Autoencoders". 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). Barcelona, Spain: IEEE. pp. 241–246. arXiv:1608.04667. Bibcode:2016arXiv160804667G. doi:10.1109/ICDMW.2016.0041. ISBN 9781509059102. S2CID 14354973.
Cho, Kyunghyun; Bart van Merrienboer; Bahdanau, Dzmitry; Bengio, Yoshua (2014). "On the Properties of Neural Machine Translation: Encoder-Decoder Approaches". arXiv:1409.1259 [cs.CL].
Sutskever, Ilya; Vinyals, Oriol; Le, Quoc V. (2014). "Sequence to Sequence Learning with Neural Networks". arXiv:1409.3215 [cs.CL].
Han, Lifeng; Kuang, Shaohui (2018). "Incorporating Chinese Radicals into Neural Machine Translation: Deeper Than Character Level". arXiv:1805.01565 [cs.CL].

deeplearningbook.org

Goodfellow, Ian; Bengio, Yoshua; Courville, Aaron (2016). Deep Learning. MIT Press. ISBN 978-0262035613.

doi.org

Bank, Dor; Koenigstein, Noam; Giryes, Raja (2023). "Autoencoders". In Rokach, Lior; Maimon, Oded; Shmueli, Erez (eds.). Machine learning for data science handbook. pp. 353–374. doi:10.1007/978-3-031-24628-9_16. ISBN 978-3-031-24627-2.
Welling, Max; Kingma, Diederik P. (2019). "An Introduction to Variational Autoencoders". Foundations and Trends in Machine Learning. 12 (4): 307–392. arXiv:1906.02691. Bibcode:2019arXiv190602691K. doi:10.1561/2200000056. S2CID 174802445.
Liou, Cheng-Yuan; Huang, Jau-Chi; Yang, Wen-Chie (2008). "Modeling word perception using the Elman network". Neurocomputing. 71 (16–18): 3150. doi:10.1016/j.neucom.2008.04.030.
Liou, Cheng-Yuan; Cheng, Wei-Chen; Liou, Jiun-Wei; Liou, Daw-Ran (2014). "Autoencoder for words". Neurocomputing. 139: 84–96. doi:10.1016/j.neucom.2013.09.055.
Kramer, Mark A. (1991). "Nonlinear principal component analysis using autoassociative neural networks" (PDF). AIChE Journal. 37 (2): 233–243. Bibcode:1991AIChE..37..233K. doi:10.1002/aic.690370209.
Hinton, G. E.; Salakhutdinov, R.R. (2006-07-28). "Reducing the Dimensionality of Data with Neural Networks". Science. 313 (5786): 504–507. Bibcode:2006Sci...313..504H. doi:10.1126/science.1127647. PMID 16873662. S2CID 1658773.
Bengio, Y. (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (8): 1795–7. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. PMID 23946944. S2CID 207178999.
Zeng, Nianyin; Zhang, Hong; Song, Baoye; Liu, Weibo; Li, Yurong; Dobaie, Abdullah M. (2018-01-17). "Facial expression recognition via learning deep sparse autoencoders". Neurocomputing. 273: 643–649. doi:10.1016/j.neucom.2017.08.043. ISSN 0925-2312.
Kramer, M. A. (1992-04-01). "Autoassociative neural networks". Computers & Chemical Engineering. Neutral network applications in chemical engineering. 16 (4): 313–328. doi:10.1016/0098-1354(92)80051-A. ISSN 0098-1354.
Oja, Erkki (1982-11-01). "Simplified neuron model as a principal component analyzer". Journal of Mathematical Biology. 15 (3): 267–273. doi:10.1007/BF00275687. ISSN 1432-1416. PMID 7153672.
Baldi, Pierre; Hornik, Kurt (1989-01-01). "Neural networks and principal component analysis: Learning from examples without local minima". Neural Networks. 2 (1): 53–58. doi:10.1016/0893-6080(89)90014-2. ISSN 0893-6080.
Rumelhart, David E.; McClelland, James L.; AU (1986). "2. A General Framework for Parallel Distributed Processing". Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations. The MIT Press. doi:10.7551/mitpress/5236.001.0001. ISBN 978-0-262-29140-8.
Elman, Jeffrey L.; Zipser, David (1988-04-01). "Learning the hidden structure of speech". The Journal of the Acoustical Society of America. 83 (4): 1615–1626. Bibcode:1988ASAJ...83.1615E. doi:10.1121/1.395916. ISSN 0001-4966. PMID 3372872.
Bourlard, H.; Kamp, Y. (1988). "Auto-association by multilayer perceptrons and singular value decomposition". Biological Cybernetics. 59 (4–5): 291–294. doi:10.1007/BF00332918. PMID 3196773. S2CID 206775335.
Hinton, G. E.; Salakhutdinov, R.R. (2006-07-28). "Reducing the Dimensionality of Data with Neural Networks". Science. 313 (5786): 504–507. Bibcode:2006Sci...313..504H. doi:10.1126/science.1127647. PMID 16873662. S2CID 1658773.
Hinton G (2009). "Deep belief networks". Scholarpedia. 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947.
Schmidhuber, Jürgen (January 2015). "Deep learning in neural networks: An overview". Neural Networks. 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003. PMID 25462637. S2CID 11715509.
Baldi, Pierre; Hornik, Kurt (1989-01-01). "Neural networks and principal component analysis: Learning from examples without local minima". Neural Networks. 2 (1): 53–58. doi:10.1016/0893-6080(89)90014-2. ISSN 0893-6080.
Ackley, D; Hinton, G; Sejnowski, T (March 1985). "A learning algorithm for boltzmann machines". Cognitive Science. 9 (1): 147–169. doi:10.1016/S0364-0213(85)80012-4.
Salakhutdinov, Ruslan; Hinton, Geoffrey (2009-07-01). "Semantic hashing". International Journal of Approximate Reasoning. Special Section on Graphical Models and Information Retrieval. 50 (7): 969–978. doi:10.1016/j.ijar.2008.11.006. ISSN 0888-613X.
Chicco, Davide; Sadowski, Peter; Baldi, Pierre (2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14. p. 533. doi:10.1145/2649387.2649442. hdl:11311/964622. ISBN 9781450328944. S2CID 207217210.
Morales-Forero, A.; Bassetto, S. (December 2019). "Case Study: A Semi-Supervised Methodology for Anomaly Detection and Diagnosis". 2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). Macao, Macao: IEEE. pp. 1031–1037. doi:10.1109/IEEM44572.2019.8978509. ISBN 978-1-7281-3804-6. S2CID 211027131.
Sakurada, Mayu; Yairi, Takehisa (December 2014). "Anomaly Detection Using Autoencoders with Nonlinear Dimensionality Reduction". Proceedings of the MLSDA 2014 2nd Workshop on Machine Learning for Sensory Data Analysis. Gold Coast, Australia QLD, Australia: ACM Press. pp. 4–11. doi:10.1145/2689746.2689747. ISBN 978-1-4503-3159-3. S2CID 14613395.
Zhou, Chong; Paffenroth, Randy C. (2017-08-04). "Anomaly Detection with Robust Deep Autoencoders". Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM. pp. 665–674. doi:10.1145/3097983.3098052. ISBN 978-1-4503-4887-4. S2CID 207557733.
Ribeiro, Manassés; Lazzaretti, André Eugênio; Lopes, Heitor Silvério (2018). "A study of deep convolutional auto-encoders for anomaly detection in videos". Pattern Recognition Letters. 105: 13–22. Bibcode:2018PaReL.105...13R. doi:10.1016/j.patrec.2017.07.016.
Buades, A.; Coll, B.; Morel, J. M. (2005). "A Review of Image Denoising Algorithms, with a New One". Multiscale Modeling & Simulation. 4 (2): 490–530. doi:10.1137/040616024. S2CID 218466166.
Gondara, Lovedeep (December 2016). "Medical Image Denoising Using Convolutional Denoising Autoencoders". 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). Barcelona, Spain: IEEE. pp. 241–246. arXiv:1608.04667. Bibcode:2016arXiv160804667G. doi:10.1109/ICDMW.2016.0041. ISBN 9781509059102. S2CID 14354973.
Zeng, Kun; Yu, Jun; Wang, Ruxin; Li, Cuihua; Tao, Dacheng (January 2017). "Coupled Deep Autoencoder for Single Image Super-Resolution". IEEE Transactions on Cybernetics. 47 (1): 27–37. doi:10.1109/TCYB.2015.2501373. ISSN 2168-2267. PMID 26625442. S2CID 20787612.
Tzu-Hsi, Song; Sanchez, Victor; Hesham, EIDaly; Nasir M., Rajpoot (2017). "Hybrid deep autoencoder with Curvature Gaussian for detection of various types of cells in bone marrow trephine biopsy images". 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). pp. 1040–1043. doi:10.1109/ISBI.2017.7950694. ISBN 978-1-5090-1172-8. S2CID 7433130.
Xu, Jun; Xiang, Lei; Liu, Qingshan; Gilmore, Hannah; Wu, Jianzhong; Tang, Jinghai; Madabhushi, Anant (January 2016). "Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images". IEEE Transactions on Medical Imaging. 35 (1): 119–130. doi:10.1109/TMI.2015.2458702. PMC 4729702. PMID 26208307.
Martinez-Murcia, Francisco J.; Ortiz, Andres; Gorriz, Juan M.; Ramirez, Javier; Castillo-Barnes, Diego (2020). "Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders". IEEE Journal of Biomedical and Health Informatics. 24 (1): 17–26. doi:10.1109/JBHI.2019.2914970. hdl:10630/28806. PMID 31217131. S2CID 195187846.
Zhavoronkov, Alex (2019). "Deep learning enables rapid identification of potent DDR1 kinase inhibitors". Nature Biotechnology. 37 (9): 1038–1040. doi:10.1038/s41587-019-0224-x. PMID 31477924. S2CID 201716327.
De, Shaunak; Maity, Abhishek; Goel, Vritti; Shitole, Sanjay; Bhattacharya, Avik (2017). "Predicting the popularity of instagram posts for a lifestyle magazine using deep learning". 2017 2nd IEEE International Conference on Communication Systems, Computing and IT Applications (CSCITA). pp. 174–177. doi:10.1109/CSCITA.2017.8066548. ISBN 978-1-5090-4381-1. S2CID 35350962.

dx.doi.org

Kramer, M. A. (1992-04-01). "Autoassociative neural networks". Computers & Chemical Engineering. Neutral network applications in chemical engineering. 16 (4): 313–328. doi:10.1016/0098-1354(92)80051-A. ISSN 0098-1354.

epfl.ch

infoscience.epfl.ch

Bourlard, H.; Kamp, Y. (1988). "Auto-association by multilayer perceptrons and singular value decomposition". Biological Cybernetics. 59 (4–5): 291–294. doi:10.1007/BF00332918. PMID 3196773. S2CID 206775335.

escholarship.org

Cottrell, Garrison W.; Munro, Paul; Zipser, David (1987). "Learning Internal Representation From Gray-Scale Images: An Example of Extensional Programming". Proceedings of the Annual Meeting of the Cognitive Science Society. 9.

github.com

"Fashion MNIST". GitHub. 2019-07-12.

handle.net

hdl.handle.net

Chicco, Davide; Sadowski, Peter; Baldi, Pierre (2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14. p. 533. doi:10.1145/2649387.2649442. hdl:11311/964622. ISBN 9781450328944. S2CID 207217210.
Martinez-Murcia, Francisco J.; Ortiz, Andres; Gorriz, Juan M.; Ramirez, Javier; Castillo-Barnes, Diego (2020). "Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders". IEEE Journal of Biomedical and Health Informatics. 24 (1): 17–26. doi:10.1109/JBHI.2019.2914970. hdl:10630/28806. PMID 31217131. S2CID 195187846.

harvard.edu

ui.adsabs.harvard.edu

Welling, Max; Kingma, Diederik P. (2019). "An Introduction to Variational Autoencoders". Foundations and Trends in Machine Learning. 12 (4): 307–392. arXiv:1906.02691. Bibcode:2019arXiv190602691K. doi:10.1561/2200000056. S2CID 174802445.
Kramer, Mark A. (1991). "Nonlinear principal component analysis using autoassociative neural networks" (PDF). AIChE Journal. 37 (2): 233–243. Bibcode:1991AIChE..37..233K. doi:10.1002/aic.690370209.
Hinton, G. E.; Salakhutdinov, R.R. (2006-07-28). "Reducing the Dimensionality of Data with Neural Networks". Science. 313 (5786): 504–507. Bibcode:2006Sci...313..504H. doi:10.1126/science.1127647. PMID 16873662. S2CID 1658773.
Elman, Jeffrey L.; Zipser, David (1988-04-01). "Learning the hidden structure of speech". The Journal of the Acoustical Society of America. 83 (4): 1615–1626. Bibcode:1988ASAJ...83.1615E. doi:10.1121/1.395916. ISSN 0001-4966. PMID 3372872.
Hinton, G. E.; Salakhutdinov, R.R. (2006-07-28). "Reducing the Dimensionality of Data with Neural Networks". Science. 313 (5786): 504–507. Bibcode:2006Sci...313..504H. doi:10.1126/science.1127647. PMID 16873662. S2CID 1658773.
Hinton G (2009). "Deep belief networks". Scholarpedia. 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947.
Ribeiro, Manassés; Lazzaretti, André Eugênio; Lopes, Heitor Silvério (2018). "A study of deep convolutional auto-encoders for anomaly detection in videos". Pattern Recognition Letters. 105: 13–22. Bibcode:2018PaReL.105...13R. doi:10.1016/j.patrec.2017.07.016.
Gondara, Lovedeep (December 2016). "Medical Image Denoising Using Convolutional Denoising Autoencoders". 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). Barcelona, Spain: IEEE. pp. 241–246. arXiv:1608.04667. Bibcode:2016arXiv160804667G. doi:10.1109/ICDMW.2016.0041. ISBN 9781509059102. S2CID 14354973.

ieee.org

ieeexplore.ieee.org

Morales-Forero, A.; Bassetto, S. (December 2019). "Case Study: A Semi-Supervised Methodology for Anomaly Detection and Diagnosis". 2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). Macao, Macao: IEEE. pp. 1031–1037. doi:10.1109/IEEM44572.2019.8978509. ISBN 978-1-7281-3804-6. S2CID 211027131.

mit.edu

direct.mit.edu

Rumelhart, David E.; McClelland, James L.; AU (1986). "2. A General Framework for Parallel Distributed Processing". Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations. The MIT Press. doi:10.7551/mitpress/5236.001.0001. ISBN 978-0-262-29140-8.

neurips.cc

proceedings.neurips.cc

Hinton, Geoffrey E; Zemel, Richard (1993). "Autoencoders, Minimum Description Length and Helmholtz Free Energy". Advances in Neural Information Processing Systems. 6. Morgan-Kaufmann.
Schwenk, Holger; Bengio, Yoshua (1997). "Training Methods for Adaptive Boosting of Neural Networks". Advances in Neural Information Processing Systems. 10. MIT Press.
Xiao, Zhisheng; Yan, Qing; Amit, Yali (2020). "Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder". Advances in Neural Information Processing Systems. 33. arXiv:2003.02977.

nih.gov

pubmed.ncbi.nlm.nih.gov

Hinton, G. E.; Salakhutdinov, R.R. (2006-07-28). "Reducing the Dimensionality of Data with Neural Networks". Science. 313 (5786): 504–507. Bibcode:2006Sci...313..504H. doi:10.1126/science.1127647. PMID 16873662. S2CID 1658773.
Bengio, Y. (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (8): 1795–7. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. PMID 23946944. S2CID 207178999.
Oja, Erkki (1982-11-01). "Simplified neuron model as a principal component analyzer". Journal of Mathematical Biology. 15 (3): 267–273. doi:10.1007/BF00275687. ISSN 1432-1416. PMID 7153672.
Elman, Jeffrey L.; Zipser, David (1988-04-01). "Learning the hidden structure of speech". The Journal of the Acoustical Society of America. 83 (4): 1615–1626. Bibcode:1988ASAJ...83.1615E. doi:10.1121/1.395916. ISSN 0001-4966. PMID 3372872.
Bourlard, H.; Kamp, Y. (1988). "Auto-association by multilayer perceptrons and singular value decomposition". Biological Cybernetics. 59 (4–5): 291–294. doi:10.1007/BF00332918. PMID 3196773. S2CID 206775335.
Hinton, G. E.; Salakhutdinov, R.R. (2006-07-28). "Reducing the Dimensionality of Data with Neural Networks". Science. 313 (5786): 504–507. Bibcode:2006Sci...313..504H. doi:10.1126/science.1127647. PMID 16873662. S2CID 1658773.
Schmidhuber, Jürgen (January 2015). "Deep learning in neural networks: An overview". Neural Networks. 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003. PMID 25462637. S2CID 11715509.
Zeng, Kun; Yu, Jun; Wang, Ruxin; Li, Cuihua; Tao, Dacheng (January 2017). "Coupled Deep Autoencoder for Single Image Super-Resolution". IEEE Transactions on Cybernetics. 47 (1): 27–37. doi:10.1109/TCYB.2015.2501373. ISSN 2168-2267. PMID 26625442. S2CID 20787612.
Xu, Jun; Xiang, Lei; Liu, Qingshan; Gilmore, Hannah; Wu, Jianzhong; Tang, Jinghai; Madabhushi, Anant (January 2016). "Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images". IEEE Transactions on Medical Imaging. 35 (1): 119–130. doi:10.1109/TMI.2015.2458702. PMC 4729702. PMID 26208307.
Martinez-Murcia, Francisco J.; Ortiz, Andres; Gorriz, Juan M.; Ramirez, Javier; Castillo-Barnes, Diego (2020). "Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders". IEEE Journal of Biomedical and Health Informatics. 24 (1): 17–26. doi:10.1109/JBHI.2019.2914970. hdl:10630/28806. PMID 31217131. S2CID 195187846.
Zhavoronkov, Alex (2019). "Deep learning enables rapid identification of potent DDR1 kinase inhibitors". Nature Biotechnology. 37 (9): 1038–1040. doi:10.1038/s41587-019-0224-x. PMID 31477924. S2CID 201716327.

ncbi.nlm.nih.gov

Xu, Jun; Xiang, Lei; Liu, Qingshan; Gilmore, Hannah; Wu, Jianzhong; Tang, Jinghai; Madabhushi, Anant (January 2016). "Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images". IEEE Transactions on Medical Imaging. 35 (1): 119–130. doi:10.1109/TMI.2015.2458702. PMC 4729702. PMID 26208307.

ntu.edu.tw

ntur.lib.ntu.edu.tw

Liou, Cheng-Yuan; Huang, Jau-Chi; Yang, Wen-Chie (2008). "Modeling word perception using the Elman network". Neurocomputing. 71 (16–18): 3150. doi:10.1016/j.neucom.2008.04.030.

psu.edu

citeseerx.ist.psu.edu

Bengio, Y. (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (8): 1795–7. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. PMID 23946944. S2CID 207178999.

researchgate.net

Kramer, Mark A. (1991). "Nonlinear principal component analysis using autoassociative neural networks" (PDF). AIChE Journal. 37 (2): 233–243. Bibcode:1991AIChE..37..233K. doi:10.1002/aic.690370209.

sciencedirect.com

Baldi, Pierre; Hornik, Kurt (1989-01-01). "Neural networks and principal component analysis: Learning from examples without local minima". Neural Networks. 2 (1): 53–58. doi:10.1016/0893-6080(89)90014-2. ISSN 0893-6080.
Baldi, Pierre; Hornik, Kurt (1989-01-01). "Neural networks and principal component analysis: Learning from examples without local minima". Neural Networks. 2 (1): 53–58. doi:10.1016/0893-6080(89)90014-2. ISSN 0893-6080.

semanticscholar.org

api.semanticscholar.org

Welling, Max; Kingma, Diederik P. (2019). "An Introduction to Variational Autoencoders". Foundations and Trends in Machine Learning. 12 (4): 307–392. arXiv:1906.02691. Bibcode:2019arXiv190602691K. doi:10.1561/2200000056. S2CID 174802445.
Hinton, G. E.; Salakhutdinov, R.R. (2006-07-28). "Reducing the Dimensionality of Data with Neural Networks". Science. 313 (5786): 504–507. Bibcode:2006Sci...313..504H. doi:10.1126/science.1127647. PMID 16873662. S2CID 1658773.
Bengio, Y. (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (8): 1795–7. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. PMID 23946944. S2CID 207178999.
Bourlard, H.; Kamp, Y. (1988). "Auto-association by multilayer perceptrons and singular value decomposition". Biological Cybernetics. 59 (4–5): 291–294. doi:10.1007/BF00332918. PMID 3196773. S2CID 206775335.
Hinton, G. E.; Salakhutdinov, R.R. (2006-07-28). "Reducing the Dimensionality of Data with Neural Networks". Science. 313 (5786): 504–507. Bibcode:2006Sci...313..504H. doi:10.1126/science.1127647. PMID 16873662. S2CID 1658773.
Schmidhuber, Jürgen (January 2015). "Deep learning in neural networks: An overview". Neural Networks. 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003. PMID 25462637. S2CID 11715509.
Chicco, Davide; Sadowski, Peter; Baldi, Pierre (2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14. p. 533. doi:10.1145/2649387.2649442. hdl:11311/964622. ISBN 9781450328944. S2CID 207217210.
Morales-Forero, A.; Bassetto, S. (December 2019). "Case Study: A Semi-Supervised Methodology for Anomaly Detection and Diagnosis". 2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). Macao, Macao: IEEE. pp. 1031–1037. doi:10.1109/IEEM44572.2019.8978509. ISBN 978-1-7281-3804-6. S2CID 211027131.
Sakurada, Mayu; Yairi, Takehisa (December 2014). "Anomaly Detection Using Autoencoders with Nonlinear Dimensionality Reduction". Proceedings of the MLSDA 2014 2nd Workshop on Machine Learning for Sensory Data Analysis. Gold Coast, Australia QLD, Australia: ACM Press. pp. 4–11. doi:10.1145/2689746.2689747. ISBN 978-1-4503-3159-3. S2CID 14613395.
Zhou, Chong; Paffenroth, Randy C. (2017-08-04). "Anomaly Detection with Robust Deep Autoencoders". Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM. pp. 665–674. doi:10.1145/3097983.3098052. ISBN 978-1-4503-4887-4. S2CID 207557733.
Buades, A.; Coll, B.; Morel, J. M. (2005). "A Review of Image Denoising Algorithms, with a New One". Multiscale Modeling & Simulation. 4 (2): 490–530. doi:10.1137/040616024. S2CID 218466166.
Gondara, Lovedeep (December 2016). "Medical Image Denoising Using Convolutional Denoising Autoencoders". 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). Barcelona, Spain: IEEE. pp. 241–246. arXiv:1608.04667. Bibcode:2016arXiv160804667G. doi:10.1109/ICDMW.2016.0041. ISBN 9781509059102. S2CID 14354973.
Zeng, Kun; Yu, Jun; Wang, Ruxin; Li, Cuihua; Tao, Dacheng (January 2017). "Coupled Deep Autoencoder for Single Image Super-Resolution". IEEE Transactions on Cybernetics. 47 (1): 27–37. doi:10.1109/TCYB.2015.2501373. ISSN 2168-2267. PMID 26625442. S2CID 20787612.
Tzu-Hsi, Song; Sanchez, Victor; Hesham, EIDaly; Nasir M., Rajpoot (2017). "Hybrid deep autoencoder with Curvature Gaussian for detection of various types of cells in bone marrow trephine biopsy images". 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). pp. 1040–1043. doi:10.1109/ISBI.2017.7950694. ISBN 978-1-5090-1172-8. S2CID 7433130.
Martinez-Murcia, Francisco J.; Ortiz, Andres; Gorriz, Juan M.; Ramirez, Javier; Castillo-Barnes, Diego (2020). "Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders". IEEE Journal of Biomedical and Health Informatics. 24 (1): 17–26. doi:10.1109/JBHI.2019.2914970. hdl:10630/28806. PMID 31217131. S2CID 195187846.
Zhavoronkov, Alex (2019). "Deep learning enables rapid identification of potent DDR1 kinase inhibitors". Nature Biotechnology. 37 (9): 1038–1040. doi:10.1038/s41587-019-0224-x. PMID 31477924. S2CID 201716327.
De, Shaunak; Maity, Abhishek; Goel, Vritti; Shitole, Sanjay; Bhattacharya, Avik (2017). "Predicting the popularity of instagram posts for a lifestyle magazine using deep learning". 2017 2nd IEEE International Conference on Communication Systems, Computing and IT Applications (CSCITA). pp. 174–177. doi:10.1109/CSCITA.2017.8066548. ISBN 978-1-5090-4381-1. S2CID 35350962.

snu.ac.kr

dm.snu.ac.kr

An, J., & Cho, S. (2015). Variational Autoencoder based Anomaly Detection using Reconstruction Probability. Special Lecture on IE, 2, 1-18.

springer.com

link.springer.com

Bank, Dor; Koenigstein, Noam; Giryes, Raja (2023). "Autoencoders". In Rokach, Lior; Maimon, Oded; Shmueli, Erez (eds.). Machine learning for data science handbook. pp. 353–374. doi:10.1007/978-3-031-24628-9_16. ISBN 978-3-031-24627-2.
Oja, Erkki (1982-11-01). "Simplified neuron model as a principal component analyzer". Journal of Mathematical Biology. 15 (3): 267–273. doi:10.1007/BF00275687. ISSN 1432-1416. PMID 7153672.

stanford.edu

web.stanford.edu

Ng, A. (2011). Sparse autoencoder. CS294A Lecture notes, 72(2011), 1-19.

torch.ch

Generating Faces with Torch, Boesen A., Larsen L. and Sonderby S.K., 2015 torch.ch/blog/2015/11/13/gan.html

toronto.edu

cs.toronto.edu

Hinton GE, Krizhevsky A, Wang SD. Transforming auto-encoders. In International Conference on Artificial Neural Networks 2011 Jun 14 (pp. 44-51). Springer, Berlin, Heidelberg.

umontreal.ca

iro.umontreal.ca

Bengio, Y. (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (8): 1795–7. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. PMID 23946944. S2CID 207178999.

wiley.com

doi.wiley.com

Ackley, D; Hinton, G; Sejnowski, T (March 1985). "A learning algorithm for boltzmann machines". Cognitive Science. 9 (1): 147–169. doi:10.1016/S0364-0213(85)80012-4.

wired.com

Gregory, Barber. "A Molecule Designed By AI Exhibits 'Druglike' Qualities". Wired.

worldcat.org

search.worldcat.org

Zeng, Nianyin; Zhang, Hong; Song, Baoye; Liu, Weibo; Li, Yurong; Dobaie, Abdullah M. (2018-01-17). "Facial expression recognition via learning deep sparse autoencoders". Neurocomputing. 273: 643–649. doi:10.1016/j.neucom.2017.08.043. ISSN 0925-2312.
Kramer, M. A. (1992-04-01). "Autoassociative neural networks". Computers & Chemical Engineering. Neutral network applications in chemical engineering. 16 (4): 313–328. doi:10.1016/0098-1354(92)80051-A. ISSN 0098-1354.
Oja, Erkki (1982-11-01). "Simplified neuron model as a principal component analyzer". Journal of Mathematical Biology. 15 (3): 267–273. doi:10.1007/BF00275687. ISSN 1432-1416. PMID 7153672.
Baldi, Pierre; Hornik, Kurt (1989-01-01). "Neural networks and principal component analysis: Learning from examples without local minima". Neural Networks. 2 (1): 53–58. doi:10.1016/0893-6080(89)90014-2. ISSN 0893-6080.
Elman, Jeffrey L.; Zipser, David (1988-04-01). "Learning the hidden structure of speech". The Journal of the Acoustical Society of America. 83 (4): 1615–1626. Bibcode:1988ASAJ...83.1615E. doi:10.1121/1.395916. ISSN 0001-4966. PMID 3372872.
Baldi, Pierre; Hornik, Kurt (1989-01-01). "Neural networks and principal component analysis: Learning from examples without local minima". Neural Networks. 2 (1): 53–58. doi:10.1016/0893-6080(89)90014-2. ISSN 0893-6080.
Salakhutdinov, Ruslan; Hinton, Geoffrey (2009-07-01). "Semantic hashing". International Journal of Approximate Reasoning. Special Section on Graphical Models and Information Retrieval. 50 (7): 969–978. doi:10.1016/j.ijar.2008.11.006. ISSN 0888-613X.
Zeng, Kun; Yu, Jun; Wang, Ruxin; Li, Cuihua; Tao, Dacheng (January 2017). "Coupled Deep Autoencoder for Single Image Super-Resolution". IEEE Transactions on Cybernetics. 47 (1): 27–37. doi:10.1109/TCYB.2015.2501373. ISSN 2168-2267. PMID 26625442. S2CID 20787612.