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Peter Tiňo

Showing results (1-10 of 14) with videos related to

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Neural Computation|March 21, 2012
Simple deterministically constructed cycle reservoirs with regular jumpsAli Rodan, Peter Tiňo
Neural Networks : the Official Journal of the International Neural Network Society|May 30, 2017
Ordinal regression based on learning vector quantizationFengzhen Tang, Peter Tiňo
Royal Society Open Science|August 31, 2023
Influence and influenceability: global directionality in directed complex networksNiall Rodgers, Peter Tiňo, Samuel Johnson
Chaos (Woodbury, N.Y.)|April 8, 2025
Linear simple cycle reservoirs at the edge of stability perform Fourier decomposition of the input driving signalsRobert Simon Fong, Boyu Li, Peter Tiňo
Physical Review. E|July 20, 2022
Network hierarchy and pattern recovery in directed sparse Hopfield networksNiall Rodgers, Peter Tiňo, Samuel Johnson
Proceedings of the National Academy of Sciences of the United States of America|March 17, 2023
Strong connectivity in real directed networksNiall Rodgers, Peter Tiňo, Samuel Johnson
Neural Networks : the Official Journal of the International Neural Network Society|August 1, 2014
Ordinal regression neural networks based on concentric hyperspheresPedro Antonio Gutiérrez, Peter Tiňo, César Hervás-Martínez
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|April 3, 2012
Degree distribution and scaling in the connecting-nearest-neighbors modelBoris Rudolf, Mária Markošová, Martin Čajági, et al.
Neuroimage|September 18, 2013
Spatial-temporal modelling of fMRI data through spatially regularized mixture of hidden process modelsYuan Shen, Stephen D Mayhew, Zoe Kourtzi, et al.
Neural Computation|March 4, 2015
The benefits of modeling slack variables in SVMsFengzhen Tang, Peter Tiňo, Pedro Antonio Gutiérrez, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Neural Computation|March 21, 2012
Simple deterministically constructed cycle reservoirs with regular jumpsAli Rodan, Peter Tiňo
Neural Networks : the Official Journal of the International Neural Network Society|May 30, 2017
Ordinal regression based on learning vector quantizationFengzhen Tang, Peter Tiňo
Royal Society Open Science|August 31, 2023
Influence and influenceability: global directionality in directed complex networksNiall Rodgers, Peter Tiňo, Samuel Johnson
Chaos (Woodbury, N.Y.)|April 8, 2025
Linear simple cycle reservoirs at the edge of stability perform Fourier decomposition of the input driving signalsRobert Simon Fong, Boyu Li, Peter Tiňo
Physical Review. E|July 20, 2022
Network hierarchy and pattern recovery in directed sparse Hopfield networksNiall Rodgers, Peter Tiňo, Samuel Johnson
Proceedings of the National Academy of Sciences of the United States of America|March 17, 2023
Strong connectivity in real directed networksNiall Rodgers, Peter Tiňo, Samuel Johnson
Neural Networks : the Official Journal of the International Neural Network Society|August 1, 2014
Ordinal regression neural networks based on concentric hyperspheresPedro Antonio Gutiérrez, Peter Tiňo, César Hervás-Martínez
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|April 3, 2012
Degree distribution and scaling in the connecting-nearest-neighbors modelBoris Rudolf, Mária Markošová, Martin Čajági, et al.
Neuroimage|September 18, 2013
Spatial-temporal modelling of fMRI data through spatially regularized mixture of hidden process modelsYuan Shen, Stephen D Mayhew, Zoe Kourtzi, et al.
Neural Computation|March 4, 2015
The benefits of modeling slack variables in SVMsFengzhen Tang, Peter Tiňo, Pedro Antonio Gutiérrez, et al.
Pageof 2