Publications associées à Densité d'un graphe

Testing Graph Clusterability: Algorithms and Lower Bounds

Mikhail Kapralov, Aidasadat Mousavifar, Ashish Hari Chiplunkar

We consider the problem of testing graph cluster structure: given access to a graph G = (V, E), can we quickly determine whether the graph can be partitioned into a few clusters with good inner conductance, or is far from any such graph? This is a generali ...

IEEE COMPUTER SOC2018

Execution Trace Graph of Dataflow Process Networks

Marco Mattavelli, Simone Casale Brunet

The paper introduces and specifies a formalism that provides complete representations of dataflow process network (DPN) program executions, by means of directed acyclic graphs. Such graphs, also known as execution trace graphs (ETG), are composed of nodes ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Finding Perfect Matchings in Bipartite Hypergraphs

Chidambaram Annamalai

Haxell's condition [14] is a natural hypergraph analog of Hall's condition, which is a well-known necessary and sufficient condition for a bipartite graph to admit a perfect matching. That is, when Haxell's condition holds it forces the existence of a perf ...

SPRINGER HEIDELBERG2018

Stationary signal processing on graphs

Pierre Vandergheynst, Nathanaël Perraudin

Graphs are a central tool in machine learning and information processing as they allow to conveniently capture the structure of complex datasets. In this context, it is of high importance to develop flexible models of signals defined over graphs or network ...

Institute of Electrical and Electronics Engineers2017

GDSP: A graphical perspective on the distributed storage systems

Michael Christoph Gastpar, Saeid Sahraei

The classical distributed storage problem can be modeled by a k-uniform complete hyper-graph where vertices represent servers and hyper-edges represent users. Hence each hyper-edge should be able to recover the full file using only the memories of the vert ...

2017

Learning time varying graphs

Pascal Frossard, Andreas Loukas, Vasilis Kalofolias

We consider the problem of inferring the hidden structure of high-dimensional dynamic systems from the perspective of graph learning. In particular, we aim at capturing the dynamic relationships between nodes by a sequence of graphs. Our approach is motiva ...

Ieee2017

Isogeny graphs of ordinary abelian varieties

Dimitar Petkov Jetchev, Benjamin Pierre Charles Wesolowski, Ernest Hunter Brooks

Fix a prime number l. Graphs of isogenies of degree a power of l are well-understood for elliptic curves, but not for higher-dimensional abelian varieties. We study the case of absolutely simple ordinary abelian varieties over a finite field. We analyse gr ...

Springer Heidelberg2017

Structured Sequence Modeling with Graph Convolutional Recurrent Networks

Pierre Vandergheynst, Xavier Bresson, Michaël Defferrard, Youngjoo Seo

This paper introduces Graph Convolutional Recurrent Network (GCRN), a deep learning model able to predict structured sequences of data. Precisely, GCRN is a generalization of classical recurrent neural networks (RNN) to data structured by an arbitrary grap ...

2017

Principal Patterns on Graphs: Discovering Coherent Structures in Datasets

Pierre Vandergheynst, Kirell Maël Benzi, Benjamin Ricaud

Graphs are now ubiquitous in almost every field of research. Recently, new research areas devoted to the analysis of graphs and data associated to their vertices have emerged. Focusing on dynamical processes, we propose a fast, robust and scalable framewor ...

Ieee-Inst Electrical Electronics Engineers Inc2016

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Densité d'un graphe

Testing Graph Clusterability: Algorithms and Lower Bounds

Execution Trace Graph of Dataflow Process Networks

Finding Perfect Matchings in Bipartite Hypergraphs

Stationary signal processing on graphs

Exploring Selection Bias by Causal Frailty Models

GDSP: A graphical perspective on the distributed storage systems

Learning time varying graphs

Isogeny graphs of ordinary abelian varieties

Structured Sequence Modeling with Graph Convolutional Recurrent Networks

Principal Patterns on Graphs: Discovering Coherent Structures in Datasets

Graph Chatbot

Chattez avec Graph Search

GDSP: A graphical perspective on the distributed storage systems

Principal Patterns on Graphs: Discovering Coherent Structures in Datasets

Finding Perfect Matchings in Bipartite Hypergraphs

Stationary signal processing on graphs

Testing Graph Clusterability: Algorithms and Lower Bounds

Exploring Selection Bias by Causal Frailty Models

Execution Trace Graph of Dataflow Process Networks

Learning time varying graphs

Isogeny graphs of ordinary abelian varieties

Structured Sequence Modeling with Graph Convolutional Recurrent Networks