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[PDF] Top 20 High dimensional Apollonian networks

Has 10000 "High dimensional Apollonian networks" found on our website. Below are the top 20 most common "High dimensional Apollonian networks".

High dimensional Apollonian networks

High dimensional Apollonian networks

... High dimensional Apollonian networks 2 ...small-world networks [1] and Barab´asi and Albert on scale-free networks [2], the research interest on complex networks as an ... Voir le document complet

10

High-dimensional dependence modelling using Bayesian networks for the degradation of civil infrastructures and other applications

High-dimensional dependence modelling using Bayesian networks for the degradation of civil infrastructures and other applications

... investigated high-dimension deterioration problems using Bayesian ...of high-dimensional ...Bayesian networks can be a versatile framework in which both statistical and probabilistic modelling ... Voir le document complet

170

Modeling High-Dimensional Audio Sequences with Recurrent Neural Networks

Modeling High-Dimensional Audio Sequences with Recurrent Neural Networks

... of high-dimensional sequences based on recurrent neural networks (RNNs) and their application to music and ...i.e. high-level information associated with observed signals, that in turn can be ... Voir le document complet

159

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks

... for high dimensional, chaotic systems using Long Short-Term Memory (LSTM) recurrent neural ...neural networks perform inference of high dimensional dynamical systems in their reduced ... Voir le document complet

32

High-dimensional probability density estimation with randomized ensembles of tree structured bayesian networks

High-dimensional probability density estimation with randomized ensembles of tree structured bayesian networks

... In this work we explore the Perturb and Com- bine idea for probability density estimation. We study a family of learning methods to infer mix- tures of large ensembles of randomly generated tree structured Bayesian ... Voir le document complet

9

Novel three-dimensional carbon nanotube networks as high performance thermal interface materials

Novel three-dimensional carbon nanotube networks as high performance thermal interface materials

... hinder the in-plane heat transfer, thus significantly degrading the thermal performance of VACNT-based TIMs. To improve the inter-tube in-plane thermal conduction within of VACNT arrays, we propose a novel three ... Voir le document complet

33

High-Dimensional Topological Data Analysis

High-Dimensional Topological Data Analysis

... • Filamentary structures and stratified spaces: 1-dimensional filamen- tary structures appear in many domains (road networks, network of blood vessels, astronomy, etc.) and can be modeled as ... Voir le document complet

22

Some statistical results in high-dimensional dependence modeling

Some statistical results in high-dimensional dependence modeling

... A classification point-of-view on conditional Kendall’s tau Abstract We show how the problem of estimating conditional Kendall’s tau can be rewritten as a classifica- tion task. Conditional Kendall’s tau is a ... Voir le document complet

305

Cliques in high-dimensional random geometric graphs

Cliques in high-dimensional random geometric graphs

... nodes. These graphs resemble real social, technological and biological networks in many aspects. Also, they might be useful in statistics and machine learning tasks: the correlations between observations in a ... Voir le document complet

25

Cliques in high-dimensional random geometric graphs

Cliques in high-dimensional random geometric graphs

... 2. Bollob´ as, B.: Random Graphs, Cambridge University press (2001). 3. Alon, N., Spencer, J. H.: The probabilistic method, John Wiley & Sons (2004). 4. Preciado, V. M., Jadbabaie, A.: Spectral analysis of virus ... Voir le document complet

11

Model selection for sparse high-dimensional learning

Model selection for sparse high-dimensional learning

... neural networks by MacKay ( 1994 ) and Neal ( 1996 ) as automatic relevance determination (ARD), it led to efficient and sparse high dimensional learning in several contexts, including kernel machines ... Voir le document complet

164

Vertex labeling and routing in expanded Apollonian networks

Vertex labeling and routing in expanded Apollonian networks

... classical Apollonian packing, Andrade et al. introduced Apollonian networks [20], which were simultaneously proposed by Doye and Massen in ...[21]. Apollonian networks belong to a class ... Voir le document complet

14

High-dimensional instrumental variables regression and confidence sets

High-dimensional instrumental variables regression and confidence sets

... unobserved networks, individual and peer outcomes can be determined simultaneously, peer identities are unobserved, and the number of peers can be small if link formation is ...exhibit high-dimensionality, ... Voir le document complet

64

Circuit-Switched Gossiping in the 3-Dimensional Torus Networks

Circuit-Switched Gossiping in the 3-Dimensional Torus Networks

... 1 Introduction D ISTRIBUTED memory multicomputer systems in which the processors communicate by exchan- ging messages over an interconnection network are a very popular method for achieving cost- effective ... Voir le document complet

24

High-dimensional intracity quantum cryptography with structured photons

High-dimensional intracity quantum cryptography with structured photons

... OCIS codes: (270.5568) Quantum cryptography; (060.2605) Free-space optical communication; (050.4865) Optical vortices. https://doi.org/10.1364/OPTICA.4.001006 1. INTRODUCTION Secure quantum communication, i.e., quantum ... Voir le document complet

6

Automated high-dimensional flow cytometric data analysis

Automated high-dimensional flow cytometric data analysis

... Some past approaches (23–25) to automated multidimensional flow cytometric analysis were restricted to supervised or nonpara- metric techniques. The unsupervised learning methodology of FLAME allows sensitive and more ... Voir le document complet

7

Scalable Collaborative Targeted Learning for High-Dimensional Data

Scalable Collaborative Targeted Learning for High-Dimensional Data

... The claim codes are manually clustered in four categories: inpatient diagnoses, outpatient diagnoses, inpatient procedures and outpatient procedures. Vytorin Data Set. The Vytorin data included all United Healthcare ... Voir le document complet

16

Kernel methods for high dimensional data analysis

Kernel methods for high dimensional data analysis

... of high dimension; large memory supplies enable to store internet datasets using a large number of features, med- ical data using a large number of parameters, etc [ 1 ], [ 2 ]; genome investigation [ 3 ],[ 4 ], ... Voir le document complet

97

Similarity Learning for High-Dimensional Sparse Data

Similarity Learning for High-Dimensional Sparse Data

... To overcome this difficulty, a common practice is to first project data into a low-dimensional space (using PCA or random projections), and then learn a similar- ity function in the reduced space. Note that the ... Voir le document complet

11

Two-dimensional phase cartography for high-harmonic spectroscopy

Two-dimensional phase cartography for high-harmonic spectroscopy

... on high-order-harmonic generation has become a powerful investigation method for attosecond dynamics in gas and solid ...allowing high-precision phase recovery using a Shack–Hartmann-like ...to high- ... Voir le document complet

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