Results 271 to 280 of about 267,735 (315)
A compact handheld GelSight probe reconstructs in vivo 3‐D skin topography with micron‐level precision using a custom elastic gel and a learning‐based surface normal to height map pipeline. The device quantifies wrinkle depth across various body locations and detects changes in wrinkle depth following moisturizer application.
Akhil Padmanabha +12 more
wiley +1 more source
Matrix-based pagerank control in hypergraphs for semantic text summaries. [PDF]
Aleja D +3 more
europepmc +1 more source
Stochastically evolving graphs via edit semigroups. [PDF]
Chung F, Robertson SJ.
europepmc +1 more source
A versatile coherent Ising computing platform. [PDF]
Wei H +14 more
europepmc +1 more source
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Random Graphs and Graph Optimization Problems
SIAM Journal on Computing, 1980One major difficulty in analyzing algorithms for graph optimization problems is that the probabilistic behavior of the optimum solutions to most of the important problems is generally unknown. We present a general method for relating some well-known results regarding the probability of existence of certain subgraphs in random graphs to the ...
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1992
Abstract In this chapter, we indicate how the general results of Chapter 2 can be used in problems involving random graphs. In Section 5.1 we consider the number of copies of a small graph G contained in Kn,p. Three cases are distinguished, counting all copies of G, induced copies of G and isolated copies of G, illustrating different ...
A D Barbour, Lars Holst, Svante Janson
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Abstract In this chapter, we indicate how the general results of Chapter 2 can be used in problems involving random graphs. In Section 5.1 we consider the number of copies of a small graph G contained in Kn,p. Three cases are distinguished, counting all copies of G, induced copies of G and isolated copies of G, illustrating different ...
A D Barbour, Lars Holst, Svante Janson
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2010
Abstract An introduction to the mathematics of the Poisson random graph, the simplest model of a random network. The chapter starts with a definition of the model, followed by derivations of basic properties like the mean degree, degree distribution, and clustering coefficient.
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Abstract An introduction to the mathematics of the Poisson random graph, the simplest model of a random network. The chapter starts with a definition of the model, followed by derivations of basic properties like the mean degree, degree distribution, and clustering coefficient.
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2001
In this second edition of the now classic text, the already extensive treatment given in the first edition has been heavily revised by the author. The addition of two new sections, numerous new results and 150 references means that this represents a comprehensive account of random graph theory. The theory (founded by Erdös and Rényi in the late fifties)
openaire +1 more source
In this second edition of the now classic text, the already extensive treatment given in the first edition has been heavily revised by the author. The addition of two new sections, numerous new results and 150 references means that this represents a comprehensive account of random graph theory. The theory (founded by Erdös and Rényi in the late fifties)
openaire +1 more source
Random Graphs, Random Triangle-Free Graphs, and Random Partial Orders
2001While everybody seems to immediately understand and accept the commonly used model of a random graph - simply toss a coin for every edge to decide whether it is there - the situation gets harder when we require that the random graph must satisfy some additional constraints such as having no triangles or being transitive.
Hans Jürgen Prömel, Anusch Taraz
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Noble-Metal Based Random Alloy and Intermetallic Nanocrystals: Syntheses and Applications
Chemical Reviews, 2021Ming Zhou, Can Li, Jiye Fang
exaly

