Concept

Lexique de la théorie des graphes

Publications associées (89)

Reduction of the sign problem near T=0 in quantum Monte Carlo simulations

Building on a recent investigation of the Shastry-Sutherland model [S. Wessel et al., Phys. Rev. B 98, 174432 (2018)], we develop a general strategy to eliminate the Monte Carlo sign problem near the zero-temperature limit in frustrated quantum spin models ...

AMER PHYSICAL SOC2020

Topological exploration of artificial neuronal network dynamics

Kathryn Hess Bellwald, Gard Spreemann

One of the paramount challenges in neuroscience is to understand the dynamics of individual neurons and how they give rise to network dynamics when interconnected. Historically, researchers have resorted to graph theory, statistics, and statistical mechani ...

MIT PRESS2019

Statistical Physics Methods for Community Detection

Chun Lam Chan

This thesis is devoted to information-theoretic aspects of community detection. The importance of community detection is due to the massive amount of scientific data today that describes relationships between items from a network, e.g., a social network. I ...

EPFL2019

Asyrnptotics for the Turan number of Berge-K-2,K-t

Abhishek Methuku

Let F be a graph. A hypergraph is called Berge-F if it can be obtained by replacing each edge in F by a hyperedge containing it. Let F be a family of graphs. The Turan number of the family Berge-F is the maximum possible number of edges in an r-uniform hyp ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2019

Resource Allocation for Underlaying Device-to-Device Communications Using Maximal Independent Sets and Knapsack Algorithm

Alper Köse

In this paper, we address the resource allocation problem of device-to-device (D2D) communications underlaying orthogonal frequency division multiple access (OFDMA) based cellular systems by exploiting the efficiency that comes from an ensemble of graph th ...

IEEE2018

Deep learning on graph for semantic segmentation of point cloud

Alexandre Thierry Robert Cherqui

This master thesis provides in-depth explanations of how deep learning and graph theory can be used together to perform pointwise classification in 3D point clouds obtained by combinations of geospatial images. That scene understanding problem arises in a ...

2018

A 2D typology generator for historical masonry elements

Katrin Beyer, Shenghan Zhang, Martin Hofmann

The mechanical response of stone masonry depends on the properties of the components and also on the typology created by the stone units and the mortar joints. While the influence of the component strength on masonry is relatively well studied, few studies ...

2018

Cortical Dysconnectivity Measured by Structural Covariance Is Associated With the Presence of Psychotic Symptoms in 22q11.2 Deletion Syndrome

Dimitri Nestor Alice Van De Ville, Maude Schneider, Marie Schaer, Maria Carmela Padula

BACKGROUND: 22q11.2 deletion syndrome (22q11DS) is the third-largest known genetic risk factor for the development of psychosis. Dysconnectivity has consistently been implicated in the physiopathology of psychosis. Structural covariance of cortical morphol ...

2018

When Stuck, Flip a Coin

Slobodan Mitrovic

Many modern services need to routinely perform tasks on a large scale. This prompts us to consider the following question: How can we design efficient algorithms for large-scale computation? In this thesis, we focus on devising a general strategy to addr ...

EPFL2018

Analytical transport network theory to guide the design of 3-D microstructural networks in energy materials: Part 1. Flow without reactions

Arata Nakajo

We present a fully analytical, heuristic model the "Analytical Transport Network Model" for steady-state, diffusive, potential flow through a 3-D network. Employing a combination of graph theory, linear algebra, and geometry, the model explicitly relates a ...

Elsevier Science Bv2017

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