Results 101 to 110 of about 233,583 (184)

A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality. [PDF]

Cogn Neurodyn, 2020
Pontes-Filho S, Lind P, Yazidi A, Zhang J, Hammer H, Mello GBM, Sandvig I, Tufte G, Nichele S.   +8 more
europepmc   +1 more source

Guaranteed Locally-Stable Macromodels of Digital Devices via Echo State Networks [PDF]

, 2006
Canavero, Flavio, Maio, Ivano Adolfo, Siviero, Claudio, Stievano, Igor Simone   +3 more
core   +1 more source

Echo state network

Scholarpedia, 2007
openaire   +1 more source

Pyramidal Graph Echo State Networks

, 2018
We analyze graph neural network models that combine iterative message-passing implemented by a function with untrained weights and graph pooling operations. In particular, we alternate randomized neural message passing with graph coarsening operations, which provide multiple views of the underlying graph.
Filippo M. Bianchi, Claudio Gallicchio, Alessio Micheli   +2 more
openaire   +2 more sources

Explainable AI and echo state networks calibrate trust in human machine interaction. [PDF]

Sci Rep
Hao S, Teng F, Hou R, Zhang L, Wu H, Qi J.   +5 more
europepmc   +1 more source

Characterization of the non-stationary nature of steady-state visual evoked potentials using echo state networks. [PDF]

PLoS One, 2019
Ibáñez-Soria D, Soria-Frisch A, Garcia-Ojalvo J, Ruffini G.   +3 more
europepmc   +1 more source

Generalization and systematicity in echo state networks

, 2008
Echo state networks (ESNs) are recurrent neural networks that can be trained efficiently because the weights of recurrent connections remain fixed at random values. Investigations of these networks' ability to generalize in sentence-processing tasks have resulted in mixed outcomes. Here, we argue that ESNs do generalize but that they are not systematic,
Frank, S.L., Čerňanský, M.
openaire   +2 more sources

Early prediction of CKD from time series data using adaptive PSO optimized echo state networks. [PDF]

Sci Rep
Anbazhagan T, Rangaswamy B.
europepmc   +1 more source

Multi-scale dynamics by adjusting the leaking rate to enhance the performance of deep echo state networks. [PDF]

Front Artif Intell
Inoue S, Nobukawa S, Nishimura H, Watanabe E, Isokawa T.   +4 more
europepmc   +1 more source

Impact of time-history terms on reservoir dynamics and prediction accuracy in echo state networks. [PDF]

Sci Rep
Ebato Y, Nobukawa S, Sakemi Y, Nishimura H, Kanamaru T, Sviridova N, Aihara K.   +6 more
europepmc   +1 more source