Pascal Frossard

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Associate Professor in the Electrical Engineering Institute at EPFL, and the Associate Dean for Research in the School of Engineering

On the choice of graph neural network architectures

Seminal works on graph neural networks have primarily targeted semi-supe...
11/13/2019 ∙ by Clément Vignac, et al. ∙ 80 ∙ share

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Isometric Transformation Invariant Graph-based Deep Neural Network

Learning transformation invariant representations of visual data is an i...
08/21/2018 ∙ by Renata Khasanova, et al. ∙ 12 ∙ share

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Mask Combination of Multi-layer Graphs for Global Structure Inference

Structure inference is an important task for network data processing and...
10/22/2019 ∙ by Eda Bayram, et al. ∙ 10 ∙ share

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Wasserstein-based Graph Alignment

We propose a novel method for comparing non-aligned graphs of different ...
03/12/2020 ∙ by Hermina Petric Maretic, et al. ∙ 8 ∙ share

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

With the advent of data science, the analysis of network or graph data h...
07/01/2019 ∙ by Xing Gao, et al. ∙ 4 ∙ share

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Hold me tight! Influence of discriminative features on deep network boundaries

Important insights towards the explainability of neural networks and the...
02/15/2020 ∙ by Guillermo Ortiz-Jiménez, et al. ∙ 4 ∙ share

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Geometric robustness of deep networks: analysis and improvement

Deep convolutional neural networks have been shown to be vulnerable to a...
11/24/2017 ∙ by Can Kanbak, et al. ∙ 0 ∙ share

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Graph learning under sparsity priors

Graph signals offer a very generic and natural representation for data t...
07/18/2017 ∙ by Hermina Petric Maretic, et al. ∙ 0 ∙ share

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Graph-Based Classification of Omnidirectional Images

Omnidirectional cameras are widely used in such areas as robotics and vi...
07/26/2017 ∙ by Renata Khasanova, et al. ∙ 0 ∙ share

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Analysis of universal adversarial perturbations

Deep networks have recently been shown to be vulnerable to universal per...
05/26/2017 ∙ by Seyed-Mohsen Moosavi-Dezfooli, et al. ∙ 0 ∙ share

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Classification regions of deep neural networks

The goal of this paper is to analyze the geometric properties of deep ne...
05/26/2017 ∙ by Alhussein Fawzi, et al. ∙ 0 ∙ share

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Learning heat diffusion graphs

Effective information analysis generally boils down to properly identify...
11/04/2016 ∙ by Dorina Thanou, et al. ∙ 0 ∙ share

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Graph-based Isometry Invariant Representation Learning

Learning transformation invariant representations of visual data is an i...
03/01/2017 ∙ by Renata Khasanova, et al. ∙ 0 ∙ share

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Light Field Super-Resolution Via Graph-Based Regularization

Light field cameras capture the 3D information in a scene with a single ...
01/09/2017 ∙ by Mattia Rossi, et al. ∙ 0 ∙ share

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Universal adversarial perturbations

Given a state-of-the-art deep neural network classifier, we show the exi...
10/26/2016 ∙ by Seyed-Mohsen Moosavi-Dezfooli, et al. ∙ 0 ∙ share

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Robustness of classifiers: from adversarial to random noise

Several recent works have shown that state-of-the-art classifiers are vu...
08/31/2016 ∙ by Alhussein Fawzi, et al. ∙ 0 ∙ share

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Multi-modal image retrieval with random walk on multi-layer graphs

The analysis of large collections of image data is still a challenging p...
07/12/2016 ∙ by Renata Khasanova, et al. ∙ 0 ∙ share

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Multi-task additive models with shared transfer functions based on dictionary learning

Additive models form a widely popular class of regression models which r...
05/19/2015 ∙ by Alhussein Fawzi, et al. ∙ 0 ∙ share

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Learning Laplacian Matrix in Smooth Graph Signal Representations

The construction of a meaningful graph plays a crucial role in the succe...
06/30/2014 ∙ by Xiaowen Dong, et al. ∙ 0 ∙ share

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Multiscale Event Detection in Social Media

Event detection has been one of the most important research topics in so...
04/25/2014 ∙ by Xiaowen Dong, et al. ∙ 0 ∙ share

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Learning parametric dictionaries for graph signals

In sparse signal representation, the choice of a dictionary often involv...
01/05/2014 ∙ by Dorina Thanou, et al. ∙ 0 ∙ share

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Manitest: Are classifiers really invariant?

Invariance to geometric transformations is a highly desirable property o...
07/23/2015 ∙ by Alhussein Fawzi, et al. ∙ 0 ∙ share

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Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds

Relationships between entities in datasets are often of multiple nature,...
03/09/2013 ∙ by Xiaowen Dong, et al. ∙ 0 ∙ share

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Analysis of classifiers' robustness to adversarial perturbations

The goal of this paper is to analyze an intriguing phenomenon recently d...
02/09/2015 ∙ by Alhussein Fawzi, et al. ∙ 0 ∙ share

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Dictionary learning for fast classification based on soft-thresholding

Classifiers based on sparse representations have recently been shown to ...
02/09/2014 ∙ by Alhussein Fawzi, et al. ∙ 0 ∙ share

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A Study of Image Analysis with Tangent Distance

The computation of the geometric transformation between a reference and ...
01/11/2014 ∙ by Elif Vural, et al. ∙ 0 ∙ share

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Image registration with sparse approximations in parametric dictionaries

We examine in this paper the problem of image registration from the new ...
01/28/2013 ∙ by Alhussein Fawzi, et al. ∙ 0 ∙ share

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Rate-Distortion Analysis of Multiview Coding in a DIBR Framework

Depth image based rendering techniques for multiview applications have b...
11/19/2012 ∙ by Boshra Rajaei, et al. ∙ 0 ∙ share

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Tangent-based manifold approximation with locally linear models

In this paper, we consider the problem of manifold approximation with af...
11/06/2012 ∙ by Sofia Karygianni, et al. ∙ 0 ∙ share

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Navigation domain representation for interactive multiview imaging

Enabling users to interactively navigate through different viewpoints of...
10/18/2012 ∙ by Thomas Maugey, et al. ∙ 0 ∙ share

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Joint Reconstruction of Multi-view Compressed Images

The distributed representation of correlated multi-view images is an imp...
06/19/2012 ∙ by Vijayaraghavan Thirumalai, et al. ∙ 0 ∙ share

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Learning Smooth Pattern Transformation Manifolds

Manifold models provide low-dimensional representations that are useful ...
12/23/2011 ∙ by Elif Vural, et al. ∙ 0 ∙ share

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Discretization of Parametrizable Signal Manifolds

Transformation-invariant analysis of signals often requires the computat...
12/23/2011 ∙ by Elif Vural, et al. ∙ 0 ∙ share

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Distributed Representation of Geometrically Correlated Images with Compressed Linear Measurements

This paper addresses the problem of distributed coding of images whose c...
11/23/2011 ∙ by Vijayaraghavan Thirumalai, et al. ∙ 0 ∙ share

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Correlation Estimation from Compressed Images

This paper addresses the problem of correlation estimation in sets of co...
07/23/2011 ∙ by Vijayaraghavan Thirumalai, et al. ∙ 0 ∙ share

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Clustering with Multi-Layer Graphs: A Spectral Perspective

Observational data usually comes with a multimodal nature, which means t...
06/11/2011 ∙ by Xiaowen Dong, et al. ∙ 0 ∙ share

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Graph-based classification of multiple observation sets

We consider the problem of classification of an object given multiple ob...
10/25/2008 ∙ by Effrosyni Kokiopoulou, et al. ∙ 0 ∙ share

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Graph-based compression of dynamic 3D point cloud sequences

This paper addresses the problem of compression of 3D point cloud sequen...
06/19/2015 ∙ by Dorina Thanou, et al. ∙ 0 ∙ share

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Adaptive Quantization for Deep Neural Network

In recent years Deep Neural Networks (DNNs) have been rapidly developed ...
12/04/2017 ∙ by Yiren Zhou, et al. ∙ 0 ∙ share

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Graph-based Transform Coding with Application to Image Compression

In this paper, we propose a new graph-based coding framework and illustr...
12/18/2017 ∙ by Giulia Fracastoro, et al. ∙ 0 ∙ share

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Online Resource Inference in Network Utility Maximization Problems

The amount of transmitted data in computer networks is expected to grow ...
11/20/2017 ∙ by Stefano D'Aronco, et al. ∙ 0 ∙ share

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Adaptive Streaming in Interactive Multiview Video Systems

Multiview applications endow final users with the possibility to freely ...
02/25/2018 ∙ by Xue Zhang, et al. ∙ 0 ∙ share

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IRSA Transmission Optimization via Online Learning

In this work, we propose a new learning framework for optimising transmi...
01/27/2018 ∙ by Laura Toni, et al. ∙ 0 ∙ share

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Optimized Data Representation for Interactive Multiview Navigation

In contrary to traditional media streaming services where a unique media...
05/08/2017 ∙ by Rui Ma, et al. ∙ 0 ∙ share

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The Sum-Rate-Distortion Region of Correlated Gauss-Markov Sources

We derive the sum-rate-distortion region for a generic number of success...
04/10/2018 ∙ by Giuseppe Cocco, et al. ∙ 0 ∙ share

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Learning Graphs from Data: A Signal Representation Perspective

The construction of a meaningful graph topology plays a crucial role in ...
06/03/2018 ∙ by Xiaowen Dong, et al. ∙ 0 ∙ share

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Graph Laplacian mixture model

Graph learning methods have recently been receiving increasing interest ...
10/23/2018 ∙ by Hermina Petric Maretic, et al. ∙ 0 ∙ share

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Multilayer Graph Signal Clustering

Multilayer graphs are commonly used to model relationships of different ...
11/02/2018 ∙ by Mireille El Gheche, et al. ∙ 0 ∙ share

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SparseFool: a few pixels make a big difference

Deep Neural Networks have achieved extraordinary results on image classi...
11/06/2018 ∙ by Apostolos Modas, et al. ∙ 0 ∙ share

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Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise

In presence of sparse noise we propose kernel regression for predicting ...
11/06/2018 ∙ by Arun Venkitaraman, et al. ∙ 0 ∙ share

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Pascal Frossard

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