Results 31 to 40 of about 2,503,125 (316)
Correlational Neural Networks [PDF]
Neural Computation, 2016 Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)–based approaches and autoencoder (AE)–based approaches.
Sarath Chandar +3 more
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Scientific Reports, 2022 Working memory (WM) is a complex cognitive function involved in the temporary storage and manipulation of information, which has been one of the target cognitive functions to be restored in neurorehabilitation.
Jimin Park +3 more
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Bootstrapping Neural Networks [PDF]
Neural Computation, 2000 Knowledge about the distribution of a statistical estimator is important for various purposes, such as the construction of confidence intervals for model parameters or the determination of critical values of tests. A widely used method to estimate this distribution is the so-called bootstrap, which is based on an imitation of the probabilistic ...
Franke, Jürgen, Neumann, Michael
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Neural Plasticity, 2004 Functional and morphological studies in children affected by Attention Deficit Hyperactivity Disorder (ADHD) suggest a prefrontal cortex (PFc) dysfunction.
D. Viggiano +3 more
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Controlling chaos in a chaotic neural network [PDF]
, 2003 The chaotic neural network constructed with chaotic neuron shows the associative memory function, but its memory searching process cannot be stabilized in a stored state because of the chaotic motion of the network.
Cao, Prof. Z. +3 more
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Interacting neural networks [PDF]
Physical Review E, 2000 Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbour. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated.
Ido Kanter +2 more
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Neural Networks proposes to reconstruct situated practices, social histories, mediating techniques, and ontological assumptions that inform the computational project of the same name. If so-called machine learning comprises a statistical approach to pattern extraction, then neural networks can be defined as a biologically inspired model that relies on ...
Dhaliwal, Ranjodh Singh +2 more
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Static internal representation of dynamic situations reveals time compaction in human cognition
Journal of Advanced Research, 2021 Introduction: The human brain has evolved under the constraint of survival in complex dynamic situations. It makes fast and reliable decisions based on internal representations of the environment.
José Antonio Villacorta-Atienza +9 more
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Frontiers in Systems Neuroscience, 2021 The hippocampus is crucial for forming associations between environmental stimuli. However, it is unclear how neural activities of hippocampal neurons dynamically change during the learning process.
Shogo Takamiya +12 more
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Neural Networks, 2003 In the last decade, the use of neural networks (NN) and of other soft computing methods has begun to spread also in the astronomical community which, due to the required accuracy of the measurements, is usually reluctant to use automatic tools to perform even the most common tasks of data reduction and data mining. The federation of heterogeneous large
CIARAMELLA A. +12 more
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