Results 61 to 70 of about 99,773 (316)
Universal approximation property of stochastic configuration networks for time series
Industrial Artificial IntelligenceFor the purpose of processing sequential data, such as time series, and addressing the challenge of manually tuning the architecture of traditional recurrent neural networks (RNNs), this paper introduces a novel approach-the Recurrent Stochastic ...
Jin-Xi Zhang, Hangyi Zhao, Xuefeng Zhang
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NanocompositesThis paper may be the first meta-analysis that presents a comprehensive synthesis of scientific works spanning the last five years, focusing on methodologies and results related to the analysis of nanocomposite using nanoparticles.
Rania Loukil +2 more
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Refinement of matching costs for stereo disparities using recurrent neural networks
EURASIP Journal on Image and Video Processing, 2021 Depth is essential information for autonomous robotics applications that need environmental depth values. The depth could be acquired by finding the matching pixels between stereo image pairs. Depth information is an inference from a matching cost volume
Alper Emlek, Murat Peker
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Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis
, 2007 This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Elsevier LtdThis Letter is concerned with the analysis problem of exponential stability for a class of discrete-time ...
Liu, Y, Liu, X, Wang, Z, Serrano, A
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Diversity and complexity in neural organoids
FEBS Letters, EarlyView.Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
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Scientific Reports, 2020 In recent years artificial neural networks achieved performance close to or better than humans in several domains: tasks that were previously human prerogatives, such as language processing, have witnessed remarkable improvements in state of the art ...
Andrea Alamia +3 more
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08041 Abstracts Collection – Recurrent Neural Networks - Models, Capacities, and Applications [PDF]
, 2008 From January 20 to 25 2008, the Dagstuhl Seminar 08041 ``Recurrent Neural Networks- Models, Capacities, and Applications'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl.
Maass, Wolfgang +3 more
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FEBS Letters, EarlyView.Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source
Segmental Recurrent Neural Networks
, 2015 We introduce segmental recurrent neural networks (SRNNs) which define, given an input sequence, a joint probability distribution over segmentations of the input and labelings of the segments. Representations of the input segments (i.e., contiguous subsequences of the input) are computed by encoding their constituent tokens using bidirectional recurrent
Lingpeng Kong, Chris Dyer, Noah A. Smith
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FEBS Letters, EarlyView.Drosophila park mutants serve as a model for Parkinson's disease. We used this strain to investigate the connection between oxidative stress and the circadian clock mechanism. We showed that increased oxidative stress affects the physiology of pacemaker cells, disrupting their daily structural plasticity. Lack of rhythmic signaling from pacemaker cells
Kamila Zientara +3 more
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