Rede neural artificial (Galician Wikipedia)

Analysis of information sources in references of the Wikipedia article "Rede neural artificial" in Galician language version.

refsWebsite

Global rank Galician rank

37doi.org

2^nd place

7^th place

11archive.org

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11arxiv.org

69^th place

154^th place

5worldcat.org

5^th place

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5nih.gov

4^th place

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5web.archive.org

1^st place

4books.google.com

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3msu.edu

1,844^th place

778^th place

3harvard.edu

18^th place

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2nips.cc

low place

1g2.com

low place

1mit.edu

415^th place

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1sciencedirect.com

149^th place

162^nd place

1degruyter.com

1,425^th place

246^th place

1umass.edu

3,341^st place

3,828^th place

1jstor.org

26^th place

72^nd place

1google.es

5,088^th place

923^rd place

1semanticscholar.org

11^th place

828^th place

1werbos.com

low place

1nature.com

234^th place

113^th place

1ufrgs.br

5,022^nd place

4,937^th place

1drive.google.com

1,343^rd place

1,260^th place

1lecun.com

low place

1witness.org

low place

1syncedreview.com

low place

1towardsdatascience.com

8,920^th place

4,040^th place

1idsia.ch

low place

9,785^th place

1fennetic.net

low place

1acm.org

1,185^th place

2,890^th place

1deeplearningbook.org

low place

1uni-bonn.de

6,912^th place

low place

1kurzweilai.net

low place

acm.org (Global: 1,185^th place; Galician: 2,890^th place)

portal.acm.org

Smolensky, P. (1986). Information processing in dynamical systems: Foundations of harmony theory. pp. 194–281. ISBN 978-0-262-68053-0.

archive.org (Global: 6^th place; Galician: 8^th place)

Bretscher, Otto (2013). Linear Algebra with Applications. Pearson. ISBN 978-0321796943.
Stigler, Stephen M. (1986). The History of Statistics: The Measurement of Uncertainty before 1900. Cambridge: Harvard. ISBN 0-674-40340-1.
Rosenblatt, F. (1958). "The Perceptron: A Probabilistic Model For Information Storage And Organization in the Brain". Psychological Review 65 (6): 386–408. doi:10.1037/h0042519.
Ivakhnenko, A. G. (1967). Cybernetics and Forecasting Techniques. American Elsevier Publishing Company. ISBN 9780444000200. ISSN 0076-9908.
Kelley, Henry J. (1960). "Gradient theory of optimal flight paths". ARS Journal 30 (10): 947–954. doi:10.2514/8.5282.
LeCun (1989). "Backpropagation Applied to Handwritten Zip Code Recognition". Neural Computation 1: 541–551.
Schmidhuber, Jürgen (1992). "Learning complex, extended sequences using the principle of history compression". Neural Computation 4 (2): 234–242. doi:10.1162/neco.1992.4.2.234.
Schmidhuber, Jürgen (1992). "Learning to control fast-weight memories: an alternative to recurrent nets". Neural Computation 4 (1): 131–139. doi:10.1162/neco.1992.4.1.131.
Srivastava, Rupesh Kumar; Greff, Klaus; Schmidhuber, Jürgen (2015). "Highway Networks". arXiv:1505.00387.
Domingos, Pedro (2015). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. ISBN 978-0465065707.
Ng, Andrew; Dean, Jeff (2012). "Building High-level Features Using Large Scale Unsupervised Learning". arXiv:1112.6209.

arxiv.org (Global: 69^th place; Galician: 154^th place)

Schmidhuber, Jürgen (2022). "Annotated History of Modern AI and Deep Learning". Cornell University. arXiv:2212.11279.
Schmidhuber, Jürgen (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks 61: 85–117. PMID 25462637. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003.
Ramachandran, Prajit; Barret, Zoph; Quoc, V. Le (2017). "Searching for Activation Functions". arXiv:1710.05941.
Schmidhuber, Jürgen (2020). "Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991)". Neural Networks 127: 58–66. PMID 32334341. arXiv:1906.04493. doi:10.1016/j.neunet.2020.04.008.
Karras,, Tero; Aila, Timo; Laine, Samuli; Lehtinen, Jaakko (2017). "Progressive Growing of GANs for Improved Quality, Stability, and Variation". Cornell University. arXiv:1710.10196.
Choromanski, Krzysztof; Likhosherstov, Valerii; Dohan, David; Song, Xingyou; Gane, Andreea; Sarlos, Tamas; Hawkins, Peter; Davis, Jared; Mohiuddin, Afroz (2020). "Rethinking Attention with Performers". arXiv:2009.14794.
Vaswani, Ashish; Shazeer, Noam; Parmar, Niki; Uszkoreit, Jakob; Jones, Llion; Gomez, Aidan N.; Kaiser, Lukasz; Polosukhin, Illia (2017). "Attention Is All You Need". arXiv:1706.03762.
Schmidhuber, Jürgen (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003.
Srivastava, Rupesh Kumar; Greff, Klaus; Schmidhuber, Jürgen (2015). "Highway Networks". arXiv:1505.00387.
Ng, Andrew; Dean, Jeff (2012). "Building High-level Features Using Large Scale Unsupervised Learning". arXiv:1112.6209.
Cireşan, Dan Claudiu; Meier, Ueli; Gambardella, Luca Maria; Schmidhuber, Jürgen (2010). "Deep, Big, Simple Neural Nets for Handwritten Digit Recognition". Neural Computation 22 (12): 3207–3220. ISSN 0899-7667. arXiv:1003.0358. doi:10.1162/neco_a_00052.

books.google.com (Global: 3^rd place; Galician: 12^th place)

The Organization of Behavior. Wiley. 1949. ISBN 978-1-135-63190-1.
Werbos, Paul John (1975). Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences. Harvard University.
Minsky, Marvin; Papert, Seymour (1969). Perceptrons: An Introduction to Computational Geometry. MIT Press. ISBN 978-0-262-63022-1.
von Leibniz, Gottfried Wilhelm Freiherr (1920). "The Early Mathematical Manuscripts of Leibniz". Open court publishing Company.

deeplearningbook.org (Global: low place; Galician: low place)

Goodfellow, Ian; Bengio, Yoshua; Courville, Aaron (2016). "Deep Learning". MIT Press.

degruyter.com (Global: 1,425^th place; Galician: 246^th place)

Kleene, S.C. (1956). "Representation of Events in Nerve Nets and Finite Automata". Annals of Mathematics Studies. Princeton University Press (34): 3–41.

doi.org (Global: 2^nd place; Galician: 7^th place)

dx.doi.org

Stigler, Stephen M. (1981). "Gauss and the Invention of Least Squares". Project Euclid 9 (3): 465–474. doi:10.1214/aos/1176345451.
Brush, Stephen G. (1967). "History of the Lenz-Ising Model". Reviews of Modern Physics 39 (4): 883–893. Bibcode:1967RvMP...39..883B. doi:10.1103/RevModPhys.39.883.
Amari, Shun-Ichi (1972). "Learning patterns and pattern sequences by self-organizing nets of threshold elements". IEEE Transactions (21): 1197–1206. ISSN 1557-9956. doi:10.1109/T-C.1972.223477.
Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences 79 (8): 2554–2558. Bibcode:1982PNAS...79.2554H. doi:10.1073/pnas.79.8.2554.
McCulloch, Warren; Pitts, Walter (1943). "A Logical Calculus of Ideas Immanent in Nervous Activity". Bulletin of Mathematical Biophysics 5 (4): 115–133. doi:10.1007/BF02478259.
Farley, B.G.; Clark, W.A. (1954). "Simulation of Self-Organizing Systems by Digital Computer". IRE Transactions on Information Theory 4 (4): 76–84. doi:10.1109/TIT.1954.1057468.
Rosenblatt, F. (1958). "The Perceptron: A Probabilistic Model For Information Storage And Organization in the Brain". Psychological Review 65 (6): 386–408. doi:10.1037/h0042519.
Olazaran, Mikel (1996). "A Sociological Study of the Official History of the Perceptrons Controversy". Social Studies of Science 26 (3): 611–659. JSTOR 285702. doi:10.1177/030631296026003005.
Schmidhuber, Jürgen (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks 61: 85–117. PMID 25462637. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003.
Robbins, H.; Monro, S. (1951). "A Stochastic Approximation Method". The Annals of Mathematical Statistics 22 (3): 400. doi:10.1214/aoms/1177729586.
Linnainmaa, Seppo (1976). "Taylor expansion of the accumulated rounding error". BIT Numerical Mathematics 16 (2): 146–160. doi:10.1007/bf01931367.
Kelley, Henry J. (1960). "Gradient theory of optimal flight paths". ARS Journal 30 (10): 947–954. doi:10.2514/8.5282.
Schmidhuber, Jürgen (2015). "Deep Learning". Scholarpedia 10 (11): 85–117. doi:10.4249/scholarpedia.32832.
Mizutani, E.; Dreyfus, S.E.; Nishio, K. (2000). "On derivation of MLP backpropagation from the Kelley-Bryson optimal-control gradient formula and its application". Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium. doi:10.1109/ijcnn.2000.857892.
Kohonen, Teuvo; Honkela, Timo (2007). "Kohonen Network". Scholarpedia 2 (1): 1568. doi:10.4249/scholarpedia.1568.
Kohonen, Teuvo (1982). "Self-Organized Formation of Topologically Correct Feature Maps". Biological Cybernetics 43 (4): 59–69. doi:10.1007/bf00337288.
von der Malsburg, C (1973). "Self-organization of orientation sensitive cells in the striate cortex". Kybernetik 14 (2): 85–100. doi:10.1007/bf00288907.
Fukushima, Kunihiko (1980). "Neocognitron: A Self-organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position". Biological Cybernetics 36 (4): 193–202. doi:10.1007/BF00344251.
Fukushima, Kunihiko (1969). "Visual feature extraction by a multilayered network of analog threshold elements". IEEE Transactions on Systems Science and Cybernetics 5 (4): 322–333. doi:10.1109/TSSC.1969.300225.
Zhang, Wei (1990). "Parallel distributed processing model with local space-invariant interconnections and its optical architecture". Applied Optics 29 (32): 4790. doi:10.1364/AO.29.004790.
LeCun, Yann; Bottou, Léon; Bengio, Yoshua; Haffner, Patrick (1998). "Gradient-based learning applied to document recognition" (PDF). Proceedings of the IEEE 86 (11): 2278–2324. doi:10.1109/5.726791. Arquivado dende o orixinal (PDF) o 30 de outubro de 2023. Consultado o 26 de abril de 2023.
Schmidhuber, Jürgen (1992). "Learning complex, extended sequences using the principle of history compression". Neural Computation 4 (2): 234–242. doi:10.1162/neco.1992.4.2.234.
Schmidhuber, Jürgen (2010). "Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990-2010)". IEEE Transactions on Autonomous Mental Development 2 (3): 230–247. doi:10.1109/TAMD.2010.2056368.
Schmidhuber, Jürgen (2020). "Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991)". Neural Networks 127: 58–66. PMID 32334341. arXiv:1906.04493. doi:10.1016/j.neunet.2020.04.008.
Schmidhuber, Jürgen (1992). "Learning to control fast-weight memories: an alternative to recurrent nets". Neural Computation 4 (1): 131–139. doi:10.1162/neco.1992.4.1.131.
Wolf, Thomas; Debut, Lysandre; Sanh, Victor (2020). "Transformers: State-of-the-Art Natural Language Processing". Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations: 38–45. doi:10.18653/v1/2020.emnlp-demos.6.
Hochreiter, Sepp; Schmidhuber, Jürgen (1997). "Long Short-Term Memory". Neural Computation 9 (8): 1735–1780. ISSN 0899-7667. PMID 9377276. doi:10.1162/neco.1997.9.8.1735.
Schmidhuber, Jürgen (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003.
Gers, Felix; Schmidhuber, Jürgen; Cummins, Fred (1999). Learning to forget: Continual prediction with LSTM 1999. 9th International Conference on Artificial Neural Networks: ICANN'99. pp. 850–855. ISBN 0-85296-721-7. doi:10.1049/cp:19991218.
He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing; Sun, Jian. Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (IEEE). pp. 770–778. ISBN 978-1-4673-8851-1. doi:10.1109/CVPR.2016.90.
Cireşan, Dan Claudiu; Meier, Ueli; Gambardella, Luca Maria; Schmidhuber, Jürgen (2010). "Deep, Big, Simple Neural Nets for Handwritten Digit Recognition". Neural Computation 22 (12): 3207–3220. ISSN 0899-7667. arXiv:1003.0358. doi:10.1162/neco_a_00052.
Scherer, Dominik; C. Müller, Andreas; Behnke, Sven (2018). "Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition" (PDF). 20th International Conference Artificial Neural Networks (ICANN): 92–101. doi:10.1007/978-3-642-15825-4_10.
Graves, A.; Liwicki, M.; Fernandez, S.; Bertolami, R.; Bunke, H.; Schmidhuber, Jürgen (2009). "A Novel Connectionist System for Unconstrained Handwriting Recognition". IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (5): 855–868. ISSN 0162-8828. PMID 19299860. doi:10.1109/tpami.2008.137.
Ciresan, Dan; Meier, U.; Schmidhuber, J. (2012). Multi-column deep neural networks for image classification. 2012 IEEE Conference on Computer Vision and Pattern Recognition. ISBN 978-1-4673-1228-8. doi:10.1109/cvpr.2012.6248110.

doi.org

Stigler, Stephen M. (1981). "Gauss and the Invention of Least Squares". Project Euclid 9 (3): 465–474. doi:10.1214/aos/1176345451.
Robbins, H.; Monro, S. (1951). "A Stochastic Approximation Method". The Annals of Mathematical Statistics 22 (3): 400. doi:10.1214/aoms/1177729586.
Schmidhuber, Jürgen (2015). "Deep Learning". Scholarpedia 10 (11): 85–117. doi:10.4249/scholarpedia.32832.

drive.google.com (Global: 1,343^rd place; Galician: 1,260^th place)

Zhang, Wei (1988). "Shift-invariant pattern recognition neural network and its optical architecture". Proceedings of Annual Conference of the Japan Society of Applied Physics.

fennetic.net (Global: low place; Galician: low place)

Mead, Carver A.; Ismail, Mohammed (1989). Analog VLSI Implementation of Neural Systems (PDF). The Kluwer International Series in Engineering and Computer Science. ISBN 978-1-4613-1639-8.

g2.com (Global: low place; Galician: low place)

learn.g2.com

Hardi Shah. "A Full Overview of Artificial Neural Networks (ANN)". learn.g2.com (en inglés).

google.es (Global: 5,088^th place; Galician: 923^rd place)

books.google.es

Ivakhnenko, A. G. (1973). Cybernetic Predicting Devices. CCM Information Corporation.

harvard.edu (Global: 18^th place; Galician: 38^th place)

adsabs.harvard.edu

Brush, Stephen G. (1967). "History of the Lenz-Ising Model". Reviews of Modern Physics 39 (4): 883–893. Bibcode:1967RvMP...39..883B. doi:10.1103/RevModPhys.39.883.
Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences 79 (8): 2554–2558. Bibcode:1982PNAS...79.2554H. doi:10.1073/pnas.79.8.2554.

ui.adsabs.harvard.edu

Karras,, Tero; Aila, Timo; Laine, Samuli; Lehtinen, Jaakko (2017). "Progressive Growing of GANs for Improved Quality, Stability, and Variation". Cornell University. arXiv:1710.10196.

idsia.ch (Global: low place; Galician: 9,785^th place)

people.idsia.ch

Hochreiter, Sepp (1991). "Untersuchungen zu dynamischen neuronalen Netzen" (PDF). Diploma thesis. Institut f. Informatik, Technische Univ. Munich. Arquivado dende o orixinal (PDF) o 2015.

jstor.org (Global: 26^th place; Galician: 72^nd place)

Olazaran, Mikel (1996). "A Sociological Study of the Official History of the Perceptrons Controversy". Social Studies of Science 26 (3): 611–659. JSTOR 285702. doi:10.1177/030631296026003005.

kurzweilai.net (Global: low place; Galician: low place)

"How bio-inspired deep learning keeps winning competitions". kurzweilai.net. Consultado o 2023.

lecun.com (Global: low place; Galician: low place)

yann.lecun.com

LeCun, Yann; Bottou, Léon; Bengio, Yoshua; Haffner, Patrick (1998). "Gradient-based learning applied to document recognition" (PDF). Proceedings of the IEEE 86 (11): 2278–2324. doi:10.1109/5.726791. Arquivado dende o orixinal (PDF) o 30 de outubro de 2023. Consultado o 26 de abril de 2023.

mit.edu (Global: 415^th place; Galician: 436^th place)

news.mit.edu

Hardesty, Larry (2017). "Explained: Neural networks". Massachisetts Institute of Technology.

msu.edu (Global: 1,844^th place; Galician: 778^th place)

cse.msu.edu

Weng, J.; Ahuja, N.; Huang, T. S. (1992). "Cresceptron: a self-organizing neural network which grows adaptively" (PDF). Proc. International Joint Conference on Neural Networks, Baltimore 1: 576–581.
Weng, J.; Ahuja, N.; Huang, T. S. (1993). "Learning recognition and segmentation of 3-D objects from 2-D images" (PDF). Proc. 4th International Conf. Computer Vision, Berlin: 121–128.
Weng, J.; Ahuja, N.; Huang, T. S. (1997). "Learning recognition and segmentation using the Cresceptron" (PDF). International Journal of Computer Vision 2: 105–139.

nature.com (Global: 234^th place; Galician: 113^th place)

Rumelhart, David E.; E. Hinton, Geoffrey; Williams, Ronald J. (1986). "Learning representations by back-propagating errors". Nature.

nih.gov (Global: 4^th place; Galician: 6^th place)

ncbi.nlm.nih.gov

Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences 79 (8): 2554–2558. Bibcode:1982PNAS...79.2554H. doi:10.1073/pnas.79.8.2554.
Schmidhuber, Jürgen (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks 61: 85–117. PMID 25462637. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003.
Schmidhuber, Jürgen (2020). "Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991)". Neural Networks 127: 58–66. PMID 32334341. arXiv:1906.04493. doi:10.1016/j.neunet.2020.04.008.
Hochreiter, Sepp; Schmidhuber, Jürgen (1997). "Long Short-Term Memory". Neural Computation 9 (8): 1735–1780. ISSN 0899-7667. PMID 9377276. doi:10.1162/neco.1997.9.8.1735.
Graves, A.; Liwicki, M.; Fernandez, S.; Bertolami, R.; Bunke, H.; Schmidhuber, Jürgen (2009). "A Novel Connectionist System for Unconstrained Handwriting Recognition". IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (5): 855–868. ISSN 0162-8828. PMID 19299860. doi:10.1109/tpami.2008.137.

nips.cc (Global: low place; Galician: low place)

papers.nips.cc

Goodfellow, Ian; Pouget-Abadie, Jean; Mirza, Mehdi; Xu,, Bing; Warde-Farley, David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua (2014). "Generative Adversarial Networks" (PDF). Proceedings of the International Conference on Neural Information Processing Systems (NIPS 2014): 2672–2680.
Srivastava, Rupesh K.; Greff, Klaus; Schmidhuber, Jürgen (2015). "Training Very Deep Networks". Curran Associates, Inc. Advances in Neural Information Processing Systems 28: 2377–2385.

sciencedirect.com (Global: 149^th place; Galician: 162^nd place)

Yang, Z.R; Yang, Z. (2014). Comprehensive Biomedical Physics. Karolinska Institute. ISBN 978-0-444-53633-4.

semanticscholar.org (Global: 11^th place; Galician: 828^th place)

Griewank, Andreas (2012). "Who Invented the Reverse Mode of Differentiation?". Optimization Stories: 389–400.

syncedreview.com (Global: low place; Galician: low place)

"GAN 2.0: NVIDIA's Hyperrealistic Face Generator". SyncedReview.com. Consultado o 2019.

towardsdatascience.com (Global: 8,920^th place; Galician: 4,040^th place)

He, Cheng (2021). "Transformer in CV". Towards Data Science. Transformer in CV. Arquivado dende o orixinal o 16 de abril de 2023. Consultado o 30 de abril de 2023.

ufrgs.br (Global: 5,022^nd place; Galician: 4,937^th place)

inf.ufrgs.br

Waibel, Alexander (1989). "Phoneme Recognition Using Time-Delay Neural Networks" (PDF). IEEE Transactions on Acoustics, Speech, and Signal Processing 37 (3): 328–339.

umass.edu (Global: 3,341^st place; Galician: 3,828^th place)

blogs.umass.edu

Rosenblatt, Frank (1957). "The Perceptron—a perceiving and recognizing automaton" (PDF). Cornell Aeronautical Laboratory. Report 85-460-1. Arquivado dende o orixinal (PDF) o 07 de abril de 2023. Consultado o 25 de abril de 2023.

uni-bonn.de (Global: 6,912^th place; Galician: low place)

ais.uni-bonn.de

Scherer, Dominik; C. Müller, Andreas; Behnke, Sven (2018). "Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition" (PDF). 20th International Conference Artificial Neural Networks (ICANN): 92–101. doi:10.1007/978-3-642-15825-4_10.

web.archive.org (Global: 1^st place; Galician: 1^st place)

Rosenblatt, Frank (1957). "The Perceptron—a perceiving and recognizing automaton" (PDF). Cornell Aeronautical Laboratory. Report 85-460-1. Arquivado dende o orixinal (PDF) o 07 de abril de 2023. Consultado o 25 de abril de 2023.
LeCun, Yann; Bottou, Léon; Bengio, Yoshua; Haffner, Patrick (1998). "Gradient-based learning applied to document recognition" (PDF). Proceedings of the IEEE 86 (11): 2278–2324. doi:10.1109/5.726791. Arquivado dende o orixinal (PDF) o 30 de outubro de 2023. Consultado o 26 de abril de 2023.
"Prepare, Don't Panic: Synthetic Media and Deepfakes". witness.org. Arquivado dende o orixinal o 2020. Consultado o 2020.
He, Cheng (2021). "Transformer in CV". Towards Data Science. Transformer in CV. Arquivado dende o orixinal o 16 de abril de 2023. Consultado o 30 de abril de 2023.
Hochreiter, Sepp (1991). "Untersuchungen zu dynamischen neuronalen Netzen" (PDF). Diploma thesis. Institut f. Informatik, Technische Univ. Munich. Arquivado dende o orixinal (PDF) o 2015.

werbos.com (Global: low place; Galician: low place)

Werbos, Paul (1982). "Applications of advances in nonlinear sensitivity analysis" (PDF). System modeling and optimization. Springer.

witness.org (Global: low place; Galician: low place)

lab.witness.org

"Prepare, Don't Panic: Synthetic Media and Deepfakes". witness.org. Arquivado dende o orixinal o 2020. Consultado o 2020.

worldcat.org (Global: 5^th place; Galician: 11^th place)

Amari, Shun-Ichi (1972). "Learning patterns and pattern sequences by self-organizing nets of threshold elements". IEEE Transactions (21): 1197–1206. ISSN 1557-9956. doi:10.1109/T-C.1972.223477.
Ivakhnenko, A. G. (1967). Cybernetics and Forecasting Techniques. American Elsevier Publishing Company. ISBN 9780444000200. ISSN 0076-9908.
Hochreiter, Sepp; Schmidhuber, Jürgen (1997). "Long Short-Term Memory". Neural Computation 9 (8): 1735–1780. ISSN 0899-7667. PMID 9377276. doi:10.1162/neco.1997.9.8.1735.
Cireşan, Dan Claudiu; Meier, Ueli; Gambardella, Luca Maria; Schmidhuber, Jürgen (2010). "Deep, Big, Simple Neural Nets for Handwritten Digit Recognition". Neural Computation 22 (12): 3207–3220. ISSN 0899-7667. arXiv:1003.0358. doi:10.1162/neco_a_00052.
Graves, A.; Liwicki, M.; Fernandez, S.; Bertolami, R.; Bunke, H.; Schmidhuber, Jürgen (2009). "A Novel Connectionist System for Unconstrained Handwriting Recognition". IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (5): 855–868. ISSN 0162-8828. PMID 19299860. doi:10.1109/tpami.2008.137.

Rede neural artificial (Galician Wikipedia)

acm.org (Global: 1,185th place; Galician: 2,890th place)

portal.acm.org

archive.org (Global: 6th place; Galician: 8th place)

arxiv.org (Global: 69th place; Galician: 154th place)

books.google.com (Global: 3rd place; Galician: 12th place)

deeplearningbook.org (Global: low place; Galician: low place)

degruyter.com (Global: 1,425th place; Galician: 246th place)

doi.org (Global: 2nd place; Galician: 7th place)

dx.doi.org

doi.org

drive.google.com (Global: 1,343rd place; Galician: 1,260th place)

fennetic.net (Global: low place; Galician: low place)

g2.com (Global: low place; Galician: low place)

learn.g2.com

google.es (Global: 5,088th place; Galician: 923rd place)

books.google.es

harvard.edu (Global: 18th place; Galician: 38th place)

adsabs.harvard.edu

ui.adsabs.harvard.edu

idsia.ch (Global: low place; Galician: 9,785th place)

people.idsia.ch

jstor.org (Global: 26th place; Galician: 72nd place)

kurzweilai.net (Global: low place; Galician: low place)

lecun.com (Global: low place; Galician: low place)

yann.lecun.com

mit.edu (Global: 415th place; Galician: 436th place)

news.mit.edu

msu.edu (Global: 1,844th place; Galician: 778th place)

cse.msu.edu

nature.com (Global: 234th place; Galician: 113th place)

nih.gov (Global: 4th place; Galician: 6th place)

ncbi.nlm.nih.gov

nips.cc (Global: low place; Galician: low place)

papers.nips.cc

sciencedirect.com (Global: 149th place; Galician: 162nd place)

semanticscholar.org (Global: 11th place; Galician: 828th place)

syncedreview.com (Global: low place; Galician: low place)

towardsdatascience.com (Global: 8,920th place; Galician: 4,040th place)

ufrgs.br (Global: 5,022nd place; Galician: 4,937th place)

inf.ufrgs.br

umass.edu (Global: 3,341st place; Galician: 3,828th place)

blogs.umass.edu

uni-bonn.de (Global: 6,912th place; Galician: low place)

ais.uni-bonn.de

web.archive.org (Global: 1st place; Galician: 1st place)

werbos.com (Global: low place; Galician: low place)

witness.org (Global: low place; Galician: low place)

lab.witness.org

worldcat.org (Global: 5th place; Galician: 11th place)

acm.org (Global: 1,185^th place; Galician: 2,890^th place)

archive.org (Global: 6^th place; Galician: 8^th place)

arxiv.org (Global: 69^th place; Galician: 154^th place)

books.google.com (Global: 3^rd place; Galician: 12^th place)

degruyter.com (Global: 1,425^th place; Galician: 246^th place)

doi.org (Global: 2^nd place; Galician: 7^th place)

drive.google.com (Global: 1,343^rd place; Galician: 1,260^th place)

google.es (Global: 5,088^th place; Galician: 923^rd place)

harvard.edu (Global: 18^th place; Galician: 38^th place)

idsia.ch (Global: low place; Galician: 9,785^th place)

jstor.org (Global: 26^th place; Galician: 72^nd place)

mit.edu (Global: 415^th place; Galician: 436^th place)

msu.edu (Global: 1,844^th place; Galician: 778^th place)

nature.com (Global: 234^th place; Galician: 113^th place)

nih.gov (Global: 4^th place; Galician: 6^th place)

sciencedirect.com (Global: 149^th place; Galician: 162^nd place)

semanticscholar.org (Global: 11^th place; Galician: 828^th place)

towardsdatascience.com (Global: 8,920^th place; Galician: 4,040^th place)

ufrgs.br (Global: 5,022^nd place; Galician: 4,937^th place)

umass.edu (Global: 3,341^st place; Galician: 3,828^th place)

uni-bonn.de (Global: 6,912^th place; Galician: low place)

web.archive.org (Global: 1^st place; Galician: 1^st place)

worldcat.org (Global: 5^th place; Galician: 11^th place)