Publications related to A Bayesian Method for Matching Two Similar Graphs without Seeds

Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We study the problem of sampling

k

-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, \ie, independent of the graph structure, and its perform ...

2015

Clustered planarity testing revisited

Radoslav Fulek, Jan Kyncl, Igor Malinovic

The Hanani--Tutte theorem is a classical result proved for the first time in the 1930s that characterizes planar graphs as graphs that admit a drawing in the plane in which every pair of edges not sharing a vertex cross an even number of times. We generali ...

2015

Graph-based denoising for time-varying point clouds

Pierre Vandergheynst, Johann Paratte, Yann Mikaël Schoenenberger

Noisy 3D point clouds arise in many applications. They may be due to errors when creating a 3D model from images or simply to imprecise depth sensors. Point clouds can be given geometrical structure using graphs created from the similarity information betw ...

2015

Chaos: Scale-out Graph Processing from Secondary Storage

Willy Zwaenepoel, Laurent Bindschaedler, Amitabha Roy, Jasmina Malicevic

Chaos scales graph processing from secondary storage to multiple machines in a cluster. Earlier systems that process graphs from secondary storage are restricted to a single ma- chine, and therefore limited by the bandwidth and capacity of the storage syst ...

2015

Reconstruction of Images from Gabor Graphs with Applications in Facial Image Processing

Graphs labeled with complex-valued Gabor jets are one of the important data formats for face recognition and the classification of facial images into medically relevant classes like genetic syndromes. We here present an interpolation rule and an iterative ...

2015

Non-Rigid Graph Registration using Active Testing Search

Pascal Fua, Raphael Sznitman, Jan Kybic, Miguel Amável Dos Santos Pinheiro

We present a new approach for matching sets of branching curvilinear structures that form graphs embedded in R2 or R3 and may be subject to deformations. Unlike earlier methods, ours does not rely on local appearance similarity nor does require a good init ...

Institute of Electrical and Electronics Engineers2015

Downsampling of Signals on Graphs Via Maximum Spanning Trees

Quy Ha Nguyen, Minh Do

Downsampling of signals living on a general weighted graph is not as trivial as of regular signals where we can simply keep every other samples. In this paper we propose a simple, yet effective downsampling scheme in which the underlying graph is approxima ...

Ieee-Inst Electrical Electronics Engineers Inc2015

MATHICSE Technical Report : Accelerated filtering on graphs using Lanczos method

Pierre Vandergheynst, Daniel Kressner, Nathanaël Perraudin, Ana Susnjara

Sinal-processing on graphs has developed into a very active field of research during the last decade. In particular, the number of applications using frames con-structed from graphs, like wavelets on graphs, has substantially increased. To attain scalabili ...

MATHICSE2015

Multi-Graph Learning of Spectral Graph Dictionaries

Pascal Frossard

We study the problem of learning constitutive features for the effective representation of graph signals, which can be considered as observations collected on different graph topologies. We propose to learn graph atoms and build graph dictionaries that pro ...

2015

Orchestration Graphs

Pierre Dillenbourg

By modeling pedagogical scenarios as directed geometrical graphs and proposing an associated modeling language, this book describes how rich learning activities, often designed for small classes, can be scaled up for use with thousands of participants. Wit ...

EPFL Press2015

A Bayesian Method for Matching Two Similar Graphs without Seeds

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Random sampling of bandlimited signals on graphs

Clustered planarity testing revisited

Graph-based denoising for time-varying point clouds

Chaos: Scale-out Graph Processing from Secondary Storage

Reconstruction of Images from Gabor Graphs with Applications in Facial Image Processing

Non-Rigid Graph Registration using Active Testing Search

Downsampling of Signals on Graphs Via Maximum Spanning Trees

MATHICSE Technical Report : Accelerated filtering on graphs using Lanczos method

Multi-Graph Learning of Spectral Graph Dictionaries

Orchestration Graphs

Reconstruction of Images from Gabor Graphs with Applications in Facial Image Processing

Clustered planarity testing revisited

Random sampling of bandlimited signals on graphs

MATHICSE Technical Report : Accelerated filtering on graphs using Lanczos method

Multi-Graph Learning of Spectral Graph Dictionaries

Non-Rigid Graph Registration using Active Testing Search

Downsampling of Signals on Graphs Via Maximum Spanning Trees

Graph-based denoising for time-varying point clouds

Chaos: Scale-out Graph Processing from Secondary Storage

Orchestration Graphs