Results 231 to 240 of about 317,020 (282)

Imaging intravoxel vessel size distribution in the brain using susceptibility contrast enhanced MRI. [PDF]

Imaging Neurosci (Camb)
Semmineh NB, Guha I, Healey D, Chandrasekharan A, Boxerman JL, Quarles CC.   +5 more
europepmc   +1 more source

Multi-label Ensemble Model for Knee Joint Anatomy and Lesion Segmentation: Segmentation of Clinical Images With Ensembling, Morphology, and Attention (SCEMA). [PDF]

Magn Reson Med
Yu AS, Yang M, Nakamura K, Lartey R, Tosun S, Subhas N, Winalski C, Chaudhary V, Li X.   +8 more
europepmc   +1 more source

BeamCraft: Deep Reinforcement Learning-DrivenMulti-Objective Beamforming for ISAC

Dao DN, Miao Y.
europepmc   +1 more source

Effects of Acute Ebselen Add-on Treatment on Resting State Function Connectivity in Depressed Patients with Inadequate Response to Antidepressants

Ramli FF, Villa LM, Martens MA, Singh N, Harmer CJ, Cowen PJ, Godlewska BR.   +6 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Convolutional Multitimescale Echo State Network

IEEE Transactions on Cybernetics, 2021
As efficient recurrent neural network (RNN) models, echo state networks (ESNs) have attracted widespread attention and been applied in many application domains in the last decade. Although they have achieved great success in modeling time series, a single ESN may have difficulty in capturing the multitimescale structures that naturally exist in ...
Qianli Ma, Enhuan Chen, Zhenxi Lin, Jiangyue Yan, Zhiwen Yu, Wing W. Y. Ng   +5 more
openaire   +4 more sources

Growing Echo-State Network With Multiple Subreservoirs

IEEE Transactions on Neural Networks and Learning Systems, 2017
An echo-state network (ESN) is an effective alternative to gradient methods for training recurrent neural network. However, it is difficult to determine the structure (mainly the reservoir) of the ESN to match with the given application. In this paper, a growing ESN (GESN) is proposed to design the size and topology of the reservoir automatically ...
Junfei, Qiao, Fanjun, Li, Honggui, Han, Wenjing, Li   +3 more
openaire   +4 more sources

fastESN: Fast Echo State Network

IEEE Transactions on Neural Networks and Learning Systems, 2023
Echo state networks (ESNs) are reservoir computing-based recurrent neural networks widely used in pattern analysis and machine intelligence applications. In order to achieve high accuracy with large model capacity, ESNs usually contain a large-sized internal layer (reservoir), making the evaluation process too slow for some applications.
Hai Wang, Xingyi Long, Xue-Xin Liu
openaire   +2 more sources

Balanced echo state networks

Neural Networks, 2012
This paper investigates the interaction between the driving output feedback and the internal reservoir dynamics in echo state networks (ESNs). The interplay is studied experimentally on the multiple superimposed oscillators (MSOs) benchmark. The experimental data reveals a dual effect of the output feedback strength on the network dynamics: it drives ...
Danil, Koryakin, Johannes, Lohmann, Martin V, Butz   +2 more
openaire   +2 more sources

Regular echo state networks

Proceedings of the 36th Annual ACM Symposium on Applied Computing, 2021
Reservoir computing is a computational paradigm derived from recurrent neural network models. One of its most representative technique is the Echo State Network (ESN), which is usually composed by two salient components: reservoir and readout. The former is responsible by mapping temporal (or sequential) inputs into a high-dimensional space and the ...
Lucas Z. Bissaro, Yaochu Jin, Murillo G. Carneiro   +2 more
openaire   +1 more source