Results 11 to 20 of about 526,995 (214)
Dimensional reduction in the sky [PDF]
Physical Review D, 2013 We explore the cosmological implications of a mechanism found in several approaches to quantum-gravity, whereby the spectral dimension of spacetime runs from the standard value of 4 in the infrared (IR) to a smaller value in the ultraviolet (UV). Specifically, we invoke the picture where the phenomenon is associated with modified dispersion relations ...
João Magueijo +4 more
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Deformed dimensional reduction
Geometry & Topology, 2022 Since its first use by Behrend, Bryan, and Szendrői in the computation of motivic Donaldson-Thomas (DT) invariants of $\mathbb{A}_{\mathbb{C}}^3$, dimensional reduction has proved to be an important tool in motivic and cohomological DT theory. Inspired by a conjecture of Cazzaniga, Morrison, Pym, and Szendrői on motivic DT invariants, work of ...
Davison, Ben, Pădurariu, Tudor
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On the dimensional reduction procedure [PDF]
Nuclear Physics B, 2001 15 pages, Latex, enlarged discussion added in Sec 3 and typos corrected. Version to appear in Nucl.
Cognola, Guido, Zerbini, Sergio
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Dimensionality reduction methods [PDF]
Advances in Methodology and Statistics, 2005 In case one or more sets of variables are available, the use of dimensional reduction methods could be necessary. In this contest, after a review on the link between the Shrinkage Regression Methods and Dimensional Reduction Methods, authors provide a different multivariate extension of the Garthwaite's PLS approach (1994) where a simple linear ...
D'AMBRA L, AMENTA P, GALLO, Michele
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Rare desynchronization events in power grids: on data implementation and dimensional reductions
Journal of Physics: Complexity, 2022 We discuss the frequency of desynchronization events in power grids for realistic data input. We focus on the role of time correlations in the fluctuating power production and propose a new method for implementing colored noise that reproduces non ...
Tim Ritmeester, Hildegard Meyer-Ortmanns
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Emergence of time persistence in a data-driven neural network model
eLife, 2023 Establishing accurate as well as interpretable models of network activity is an open challenge in systems neuroscience. Here, we infer an energy-based model of the anterior rhombencephalic turning region (ARTR), a circuit that controls zebrafish swimming
Sebastien Wolf +4 more
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IEEE Open Journal of Instrumentation and Measurement, 2022 Deep learning neural network serves as a powerful tool for visual anomaly detection (AD) and fault diagnosis, attributed to its strong abstractive interpretation ability in the representation domain.
Jie Lin, Song Chen, Enping Lin, Yu Yang
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Compressing Fisher Vector for Robust Face Recognition
IEEE Access, 2017 One major topic for robust face recognition could be the efficient encoding of facial descriptors. Among various encoders, Fisher vector (FV) is one of the probabilistic methods that yield promising results.
Hongjun Wang, Jiani Hu, Weihong Deng
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Weighted Kernel Entropy Component Analysis for Fault Diagnosis of Rolling Bearings
Sensors, 2017 This paper presents a supervised feature extraction method called weighted kernel entropy component analysis (WKECA) for fault diagnosis of rolling bearings.
Hongdi Zhou +7 more
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SAELGMDA: Identifying human microbe–disease associations based on sparse autoencoder and LightGBM
Frontiers in Microbiology, 2023 IntroductionIdentification of complex associations between diseases and microbes is important to understand the pathogenesis of diseases and design therapeutic strategies.
Feixiang Wang +5 more
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