Publications related to Cubic graph

Electricity Theft Detection Using Dynamic Graph Construction and Graph Attention Network

Wenlong Liao, Bin Zhang, Zhe Yang, Bin Feng

The integrations of advanced metering infrastructure and smart meters make it possible to detect electricity thieves by analyzing electricity consumption readings. However, the detection accuracies of traditional models are limited due to their difficulty ...

Piscataway2023

Frequent asymmetric migrations suppress natural selection in spatially structured populations

Anne-Florence Raphaëlle Bitbol, Alia Abbara

Natural microbial populations often have complex spatial structures. This can impact their evolution, in particular the ability of mutants to take over. While mutant fixation probabilities are known to be unaffected by sufficiently symmetric structures, ev ...

Oxford2023

Nature vs. Nurture: Feature vs. Structure for Graph Neural Networks

Karl Aberer, Thành Tâm Nguyên, Chi Thang Duong

Graph neural networks take node features and graph structure as input to build representations for nodes and graphs. While there are a lot of focus on GNN models, understanding the impact of node features and graph structure to GNN performance has received ...

ELSEVIER2022

iPool--Information-Based Pooling in Hierarchical Graph Neural Networks

Pascal Frossard, Chenglin Li, Xing Gao

With the advent of data science, the analysis of network or graph data has become a very timely research problem. A variety of recent works have been proposed to generalize neural networks to graphs, either from a spectral graph theory or a spatial perspec ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Partition and Code: learning how to compress graphs

Michael Bronstein, Andreas Loukas, Nikolaos Karalias, Georgios Bouritsas

Can we use machine learning to compress graph data? The absence of ordering in graphs poses a significant challenge to conventional compression algorithms, limiting their attainable gains as well as their ability to discover relevant patterns. On the other ...

2021

Experiments with the Markoff Surface

Matthew De Courcy-Ireland, Sandy Lee

We confirm, for the primes up to 3000, the conjecture of Bourgain-Gamburd-Sarnak and Baragar on strong approximation for the Markoff surface modulo primes. For primes congruent to 3 modulo 4, we find data suggesting that some natural graphs constructed fro ...

TAYLOR & FRANCIS INC2020

Local approximation of the Maximum Cut in regular graphs

Etienne Michel François Bamas

This paper is devoted to the distributed complexity of finding an approximation of the maximum cut (MAXCUT) in graphs. A classical algorithm consists in letting each vertex choose its side of the cut uniformly at random. This does not require any communica ...

ELSEVIER2020

Time-resolved analysis of dynamic graphs: an extended Slepian design

Dimitri Nestor Alice Van De Ville, Raphaël Pierre Liégeois, Ibrahim Merad

Graphs are extensively used to represent networked data. In many applications, especially when considering large datasets, it is a desirable feature to focus the analysis onto specific subgraphs of interest. Slepian theory and its extension to graphs allow ...

SPIE-INT SOC OPTICAL ENGINEERING2019

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Cubic graph

Electricity Theft Detection Using Dynamic Graph Construction and Graph Attention Network

Frequent asymmetric migrations suppress natural selection in spatially structured populations

Metastability of the Potts Ferromagnet on Random Regular Graphs

Nature vs. Nurture: Feature vs. Structure for Graph Neural Networks

iPool--Information-Based Pooling in Hierarchical Graph Neural Networks

Partition and Code: learning how to compress graphs

The Schur-Erdos problem for sesmi-algebraic colorings

Experiments with the Markoff Surface

Local approximation of the Maximum Cut in regular graphs

Time-resolved analysis of dynamic graphs: an extended Slepian design

Graph Chatbot

Chat with Graph Search

Experiments with the Markoff Surface

Time-resolved analysis of dynamic graphs: an extended Slepian design

Electricity Theft Detection Using Dynamic Graph Construction and Graph Attention Network

iPool--Information-Based Pooling in Hierarchical Graph Neural Networks

Partition and Code: learning how to compress graphs

Local approximation of the Maximum Cut in regular graphs

Metastability of the Potts Ferromagnet on Random Regular Graphs

Nature vs. Nurture: Feature vs. Structure for Graph Neural Networks

Frequent asymmetric migrations suppress natural selection in spatially structured populations

The Schur-Erdos problem for sesmi-algebraic colorings