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Echo state network (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Echo state network" in English language version.

refsWebsite
Global rank English rank
13doi.org
2nd place
2nd place
10semanticscholar.org
11th place
8th place
8nih.gov
4th place
4th place
5harvard.edu
18th place
17th place
4arxiv.org
69th place
59th place
1columbia.edu
488th place
374th place
1psu.edu
207th place
136th place

arxiv.org

columbia.edu

  • Jaeger, H.; Haas, H. (2004). "Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication" (PDF). Science. 304 (5667): 78–80. Bibcode:2004Sci...304...78J. doi:10.1126/science.1091277. PMID 15064413. S2CID 2184251.

doi.org

  • Jaeger, H.; Haas, H. (2004). "Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication" (PDF). Science. 304 (5667): 78–80. Bibcode:2004Sci...304...78J. doi:10.1126/science.1091277. PMID 15064413. S2CID 2184251.
  • Jaeger, Herbert (2007). "Echo state network". Scholarpedia. 2 (9): 2330. Bibcode:2007SchpJ...2.2330J. doi:10.4249/scholarpedia.2330.
  • Chatzis, S. P.; Demiris, Y. (2011). "Echo State Gaussian Process". IEEE Transactions on Neural Networks. 22 (9): 1435–1445. doi:10.1109/TNN.2011.2162109. PMID 21803684. S2CID 8553623.
  • Antonik, Piotr; Gulina, Marvyn; Pauwels, Jaël; Massar, Serge (2018). "Using a reservoir computer to learn chaotic attractors, with applications to chaos synchronization and cryptography". Phys. Rev. E. 98 (1): 012215. arXiv:1802.02844. Bibcode:2018PhRvE..98a2215A. doi:10.1103/PhysRevE.98.012215. PMID 30110744. S2CID 3616565.
  • Maass W., Natschlaeger T., and Markram H. (2002). "Real-time computing without stable states: A new framework for neural computation based on perturbations". Neural Computation. 14 (11): 2531–2560. doi:10.1162/089976602760407955. PMID 12433288. S2CID 1045112.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Schiller U.D. and Steil J. J. (2005). "Analyzing the weight dynamics of recurrent learning algorithms". Neurocomputing. 63: 5–23. doi:10.1016/j.neucom.2004.04.006.
  • Dominey P.F. (1995). "Complex sensory-motor sequence learning based on recurrent state representation and reinforcement learning". Biol. Cybernetics. 73 (3): 265–274. doi:10.1007/BF00201428. PMID 7548314. S2CID 1603500.
  • Buonomano, D.V. and Merzenich, M.M. (1995). "Temporal Information Transformed into a Spatial Code by a Neural Network with Realistic Properties". Science. 267 (5200): 1028–1030. Bibcode:1995Sci...267.1028B. doi:10.1126/science.7863330. PMID 7863330. S2CID 12880807.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Schomaker, L. (1992). "A neural oscillator-network model of temporal pattern generation". Human Movement Science. 11 (1–2): 181–192. doi:10.1016/0167-9457(92)90059-K.
  • Schmidhuber J., Gomez F., Wierstra D., and Gagliolo M. (2007). "Training recurrent networks by evolino". Neural Computation. 19 (3): 757–779. CiteSeerX 10.1.1.218.3086. doi:10.1162/neco.2007.19.3.757. PMID 17298232. S2CID 11745761.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Doan N, Polifke W, Magri L (2020). "Physics-Informed Echo State Networks". Journal of Computational Science. 47: 101237. arXiv:2011.02280. doi:10.1016/j.jocs.2020.101237. S2CID 226246385.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Pathak J, Wikner A, Russel R, Chandra S, Hunt B, Girvan M, Ott E (2018). "Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model". Chaos. 28 (4): 041101. arXiv:1803.04779. Bibcode:2018Chaos..28d1101P. doi:10.1063/1.5028373. PMID 31906641. S2CID 3883587.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Doya K. (1992). "Bifurcations in the learning of recurrent neural networks". [Proceedings] 1992 IEEE International Symposium on Circuits and Systems. Vol. 6. pp. 2777–2780. doi:10.1109/ISCAS.1992.230622. ISBN 0-7803-0593-0. S2CID 15069221.

harvard.edu

ui.adsabs.harvard.edu

  • Jaeger, H.; Haas, H. (2004). "Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication" (PDF). Science. 304 (5667): 78–80. Bibcode:2004Sci...304...78J. doi:10.1126/science.1091277. PMID 15064413. S2CID 2184251.
  • Jaeger, Herbert (2007). "Echo state network". Scholarpedia. 2 (9): 2330. Bibcode:2007SchpJ...2.2330J. doi:10.4249/scholarpedia.2330.
  • Antonik, Piotr; Gulina, Marvyn; Pauwels, Jaël; Massar, Serge (2018). "Using a reservoir computer to learn chaotic attractors, with applications to chaos synchronization and cryptography". Phys. Rev. E. 98 (1): 012215. arXiv:1802.02844. Bibcode:2018PhRvE..98a2215A. doi:10.1103/PhysRevE.98.012215. PMID 30110744. S2CID 3616565.
  • Buonomano, D.V. and Merzenich, M.M. (1995). "Temporal Information Transformed into a Spatial Code by a Neural Network with Realistic Properties". Science. 267 (5200): 1028–1030. Bibcode:1995Sci...267.1028B. doi:10.1126/science.7863330. PMID 7863330. S2CID 12880807.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Pathak J, Wikner A, Russel R, Chandra S, Hunt B, Girvan M, Ott E (2018). "Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model". Chaos. 28 (4): 041101. arXiv:1803.04779. Bibcode:2018Chaos..28d1101P. doi:10.1063/1.5028373. PMID 31906641. S2CID 3883587.{{cite journal}}: CS1 maint: multiple names: authors list (link)

nih.gov

pubmed.ncbi.nlm.nih.gov

  • Jaeger, H.; Haas, H. (2004). "Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication" (PDF). Science. 304 (5667): 78–80. Bibcode:2004Sci...304...78J. doi:10.1126/science.1091277. PMID 15064413. S2CID 2184251.
  • Chatzis, S. P.; Demiris, Y. (2011). "Echo State Gaussian Process". IEEE Transactions on Neural Networks. 22 (9): 1435–1445. doi:10.1109/TNN.2011.2162109. PMID 21803684. S2CID 8553623.
  • Antonik, Piotr; Gulina, Marvyn; Pauwels, Jaël; Massar, Serge (2018). "Using a reservoir computer to learn chaotic attractors, with applications to chaos synchronization and cryptography". Phys. Rev. E. 98 (1): 012215. arXiv:1802.02844. Bibcode:2018PhRvE..98a2215A. doi:10.1103/PhysRevE.98.012215. PMID 30110744. S2CID 3616565.
  • Maass W., Natschlaeger T., and Markram H. (2002). "Real-time computing without stable states: A new framework for neural computation based on perturbations". Neural Computation. 14 (11): 2531–2560. doi:10.1162/089976602760407955. PMID 12433288. S2CID 1045112.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Dominey P.F. (1995). "Complex sensory-motor sequence learning based on recurrent state representation and reinforcement learning". Biol. Cybernetics. 73 (3): 265–274. doi:10.1007/BF00201428. PMID 7548314. S2CID 1603500.
  • Buonomano, D.V. and Merzenich, M.M. (1995). "Temporal Information Transformed into a Spatial Code by a Neural Network with Realistic Properties". Science. 267 (5200): 1028–1030. Bibcode:1995Sci...267.1028B. doi:10.1126/science.7863330. PMID 7863330. S2CID 12880807.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Schmidhuber J., Gomez F., Wierstra D., and Gagliolo M. (2007). "Training recurrent networks by evolino". Neural Computation. 19 (3): 757–779. CiteSeerX 10.1.1.218.3086. doi:10.1162/neco.2007.19.3.757. PMID 17298232. S2CID 11745761.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Pathak J, Wikner A, Russel R, Chandra S, Hunt B, Girvan M, Ott E (2018). "Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model". Chaos. 28 (4): 041101. arXiv:1803.04779. Bibcode:2018Chaos..28d1101P. doi:10.1063/1.5028373. PMID 31906641. S2CID 3883587.{{cite journal}}: CS1 maint: multiple names: authors list (link)

psu.edu

citeseerx.ist.psu.edu

semanticscholar.org

api.semanticscholar.org

  • Jaeger, H.; Haas, H. (2004). "Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication" (PDF). Science. 304 (5667): 78–80. Bibcode:2004Sci...304...78J. doi:10.1126/science.1091277. PMID 15064413. S2CID 2184251.
  • Chatzis, S. P.; Demiris, Y. (2011). "Echo State Gaussian Process". IEEE Transactions on Neural Networks. 22 (9): 1435–1445. doi:10.1109/TNN.2011.2162109. PMID 21803684. S2CID 8553623.
  • Antonik, Piotr; Gulina, Marvyn; Pauwels, Jaël; Massar, Serge (2018). "Using a reservoir computer to learn chaotic attractors, with applications to chaos synchronization and cryptography". Phys. Rev. E. 98 (1): 012215. arXiv:1802.02844. Bibcode:2018PhRvE..98a2215A. doi:10.1103/PhysRevE.98.012215. PMID 30110744. S2CID 3616565.
  • Maass W., Natschlaeger T., and Markram H. (2002). "Real-time computing without stable states: A new framework for neural computation based on perturbations". Neural Computation. 14 (11): 2531–2560. doi:10.1162/089976602760407955. PMID 12433288. S2CID 1045112.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Dominey P.F. (1995). "Complex sensory-motor sequence learning based on recurrent state representation and reinforcement learning". Biol. Cybernetics. 73 (3): 265–274. doi:10.1007/BF00201428. PMID 7548314. S2CID 1603500.
  • Buonomano, D.V. and Merzenich, M.M. (1995). "Temporal Information Transformed into a Spatial Code by a Neural Network with Realistic Properties". Science. 267 (5200): 1028–1030. Bibcode:1995Sci...267.1028B. doi:10.1126/science.7863330. PMID 7863330. S2CID 12880807.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Schmidhuber J., Gomez F., Wierstra D., and Gagliolo M. (2007). "Training recurrent networks by evolino". Neural Computation. 19 (3): 757–779. CiteSeerX 10.1.1.218.3086. doi:10.1162/neco.2007.19.3.757. PMID 17298232. S2CID 11745761.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Doan N, Polifke W, Magri L (2020). "Physics-Informed Echo State Networks". Journal of Computational Science. 47: 101237. arXiv:2011.02280. doi:10.1016/j.jocs.2020.101237. S2CID 226246385.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Pathak J, Wikner A, Russel R, Chandra S, Hunt B, Girvan M, Ott E (2018). "Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model". Chaos. 28 (4): 041101. arXiv:1803.04779. Bibcode:2018Chaos..28d1101P. doi:10.1063/1.5028373. PMID 31906641. S2CID 3883587.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  • Doya K. (1992). "Bifurcations in the learning of recurrent neural networks". [Proceedings] 1992 IEEE International Symposium on Circuits and Systems. Vol. 6. pp. 2777–2780. doi:10.1109/ISCAS.1992.230622. ISBN 0-7803-0593-0. S2CID 15069221.