4.6k citations · 7.9k across the 144 of their papers we have counts for
12 papers · 1 filter
Imperceptible Adversarial Attacks on Tabular Data
Vincent Ballet, Xavier Renard, Jonathan Aigrain +3
Security of machine learning models is a concern as they may face adversarial attacks for unwarranted advantageous decisions. While research on the topic has mainly been focusing o…
Joint Graph-based Depth Refinement and Normal Estimation
Mattia Rossi, Mireille El Gheche, Andreas Kuhn +1
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…
Multi-view shape estimation of transparent containers
Alessio Xompero, Ricardo Sanchez-Matilla, Apostolos Modas +2
The 3D localisation of an object and the estimation of its properties, such as shape and dimensions, are challenging under varying degrees of transparency and lighting conditions.…
On the choice of graph neural network architectures
Clément Vignac, Guillermo Ortiz-Jiménez, Pascal Frossard
Seminal works on graph neural networks have primarily targeted semi-supervised node classification problems with few observed labels and high-dimensional signals. With the developm…
Mask Combination of Multi-layer Graphs for Global Structure Inference
Eda Bayram, Dorina Thanou, Elif Vural +1
Structure inference is an important task for network data processing and analysis in data science. In recent years, quite a few approaches have been developed to learn the graph st…
Optimized Quantization in Distributed Graph Signal Filtering
Isabela Cunha Maia Nobre, Pascal Frossard
Distributed graph signal processing algorithms require the network nodes to communicate by exchanging messages in order to achieve a common objective. These messages have a finite…
Forward-Backward Splitting for Optimal Transport based Problems
Guillermo Ortiz-Jimenez, Mireille El Gheche, Effrosyni Simou +2
Optimal transport aims to estimate a transportation plan that minimizes a displacement cost. This is realized by optimizing the scalar product between the sought plan and the given…
iPool -- Information-based Pooling in Hierarchical Graph Neural Networks
Xing Gao, Hongkai Xiong, Pascal Frossard
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…
GOT: An Optimal Transport framework for Graph comparison
Hermina Petric Maretic, Mireille EL Gheche, Giovanni Chierchia +1
We present a novel framework based on optimal transport for the challenging problem of comparing graphs. Specifically, we exploit the probabilistic distribution of smooth graph sig…
A geometry-inspired decision-based attack
Yujia Liu, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard
Deep neural networks have recently achieved tremendous success in image classification. Recent studies have however shown that they are easily misled into incorrect classification…
Graph heat mixture model learning
Hermina Petric Maretic, Mireille El Gheche, Pascal Frossard
Graph inference methods have recently attracted a great interest from the scientific community, due to the large value they bring in data interpretation and analysis. However, most…
Visual Distortions in 360-degree Videos
Roberto G. de A. Azevedo, Neil Birkbeck, Francesca De Simone +3
Omnidirectional (or 360-degree) images and videos are emergent signals in many areas such as robotics and virtual/augmented reality. In particular, for virtual reality, they allow…