Results 11 to 20 of about 489,349 (320)
Scholarpedia, 2008 The(frequently updated) original version is avalable at http://www.scholarpedia.org/article ...
Peter Földiák, Dominik M. Endres
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Magnetic-Sparseness and Schrödinger Operators on Graphs [PDF]
Annales de l'Institute Henri Poincare. Physique theorique, 2017 We study magnetic Schrödinger operators on graphs. We extend the notion of sparseness of graphs by including a magnetic quantity called the frustration index.
M. Bonnefont +4 more
semanticscholar +2 more sources
Estimating optimal sparseness of developmental gene networks using a semi-quantitative model. [PDF]
PLoS ONE, 2017 To estimate gene regulatory networks, it is important that we know the number of connections, or sparseness of the networks. It can be expected that the robustness to perturbations is one of the factors determining the sparseness.
Natsuhiro Ichinose +2 more
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Selectivity and sparseness in randomly connected balanced networks.
PLoS ONE, 2014 Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected.
Cengiz Pehlevan, Haim Sompolinsky
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Representational sparseness and aesthetic evaluations of visual stimuli (power analyses)
, 2022 Power analyses for "Representational sparseness and aesthetic evaluations of visual ...
Benedict C. Jones +1 more
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Proportionate NSAF algorithms with sparseness-measured for acoustic echo cancellation
AEU - International Journal of Electronics and Communications, 2017 Yi Yu
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Frontiers in Human Neuroscience, 2014 Entrained behavior coordinates, predicts, and modulates multi-scale rhythmic gestures with high spatio-temporal precision even as it shows flexible adaptation in response to perturbation (Clayton et al., 2005; Altenmuller et al., 2006; Phillips-Silver et al., 2010).
Eric eBarnhill, Eric eBarnhill
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Sparse Convolution for Approximate Sparse Instance
CoRR, 2023 Computing the convolution $A \star B$ of two vectors of dimension $n$ is one of the most important computational primitives in many fields. For the non-negative convolution scenario, the classical solution is to leverage the Fast Fourier Transform whose time complexity is $O(n \log n)$.
Xiaoxiao Li +2 more
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Dissipativity Analysis of Large-Scale Networked Systems
Applied Sciences, 2023 This paper investigates the dissipativity analysis of large-scale networked systems with linear time-invariant dynamics. The networked system is composed of a large number of subsystems whose connections are arbitrary, and each subsystem can have ...
Yuanfei Sun, Jirong Wang, Huabo Liu
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Realization of Spatial Sparseness by Deep ReLU Nets With Massive Data [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2019 The great success of deep learning poses urgent challenges for understanding its working mechanism and rationality. The depth, structure, and massive size of the data are recognized to be three key ingredients for deep learning.
C. Chui +3 more
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