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Concept

Glossary of graph theory

Related publications (27)

Towards an Understanding of Hydraulic Sensitivity: Graph Theory Contributions to Water Distribution Analysis

Jérôme Chenal

Water distribution systems (WDSs) are complex networks with numerous interconnected junctions and pipes. The robustness and reliability of these systems are critically dependent on their network structure, necessitating detailed analysis for proactive leak ...

MDPI2024

Molecular hypergraph neural networks

Philippe Schwaller, Junwu Chen

Graph neural networks (GNNs) have demonstrated promising performance across various chemistry-related tasks. However, conventional graphs only model the pairwise connectivity in molecules, failing to adequately represent higher order connections, such as m ...

Aip Publishing2024

Better Trees for Santa Claus

Etienne Michel François Bamas, Lars Rohwedder

We revisit the problem max-min degree arborescence, which was introduced by Bateni et al. [STOC'09] as a central special case of the general Santa Claus problem, which constitutes a notorious open question in approximation algorithms. In the former problem ...

Assoc Computing Machinery2023

Unambiguous DNFs and Alon-Saks-Seymour

Mika Tapani Göös, Siddhartha Jain

We exhibit an unambiguous k-DNF formula that requires CNF width (Omega) over tilde (k(2)), which is optimal up to logarithmic factors. As a consequence, we get a near-optimal solution to the Alon-Saks-Seymour problem in graph theory (posed in 1991), which ...

IEEE COMPUTER SOC2022

The Paris/Geneva Divide. A Network Analysis of the Archives of the International Committee on Intellectual Cooperation of the League of Nations

The International Committee on Intellectual Cooperation (ICIC) is often framed as a step in the constitution of a “League of Minds” – a place where scientists and writers reign, and a necessary part of a successful and harmonious “League of Nations” – but ...

De Gruyter2022

Space-Efficient Representations of Graphs

Jakab Tardos

With the increasing prevalence of massive datasets, it becomes important to design algorithmic techniques for dealing with scenarios where the input to be processed does not fit in the memory of a single machine. Many highly successful approaches have emer ...

EPFL2022

Screw vs. edge dislocation strengthening in body-centered-cubic high entrophy alloys and implications for guided alloy design

William Curtin, Francesco Maresca, Carolina Baruffi

Body-centered-cubic (BCC) high entropy alloys (HEAs) can show exceptionally high strength up to high temperatures. Mechanistic theories are needed to guide alloy discovery within the immense multicomponent HEA compositional space. Here, two new theories fo ...

SPRINGER HEIDELBERG2022

Joint Graph-based Depth Refinement and Normal Estimation

Pascal Frossard, Mireille El Gheche, Mattia Rossi

Depth estimation is an essential component in understanding the 3D geometry of a scene, with numerous applications in urban and indoor settings. These scenes are characterized by a prevalence of human made structures, which in most of the cases, are either ...

2020

Exceptional graphs for the random walk

Juhan Aru

If W is the simple random walk on the square lattice Z(2), then W induces a random walk W-G on any spanning subgraph G subset of Z(2) of the lattice as follows: viewing W as a uniformly random infinite word on the alphabet {x, -x, y, -y}, the walk W-G star ...

INST MATHEMATICAL STATISTICS2020

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

Frédéric Mila, Jonathan D'Emidio

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 ...

2020

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 ...

2019

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. ...

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

A 2D typology generator for historical masonry elements

Katrin Beyer, Shenghan Zhang

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, Marie Schaer, Maude Schneider

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 : New Algorithms for Large-Scale Tasks

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

Graph-based Methods for Visualization and Clustering

Johann Paratte

The amount of data that we produce and consume is larger than it has been at any point in the history of mankind, and it keeps growing exponentially. All this information, gathered in overwhelming volumes, often comes with two problematic characteristics: ...

EPFL2017

Spatial clustering for district heating integration in urban energy systems: application to geothermal energy

François Maréchal, Stéphane Joost, Stefano Moret, Jérémy Michel Pierre Unternährer

Given the challenges related to climate change and dependency from fossil fuels, modification of the energy systems infrastructure to increase the share of renewable energy is a priority in urban energy planning. The high heating density in cities makes it ...

2017