Publications

Sciences de l'ingénieur

CAD Model Segmentation Via Deep Learning

Computer aided design (CAD) models are widely employed in the current computer aided engineering or finite element analysis (FEA) systems that necessitate an optimal meshing as a function of their geometry. To this effect, the sub-mapping method is…

David Bassir, Antoine van Biesbroeck, Feifei Shang

International Journal of Computational Methods - 2021

Réseau de neurones

Fast, nonlocal and neural: a lightweight high quality solution to image denoising

With the widespread application of convolutional neural networks (CNNs), the traditional model based denoising algorithms are now outperformed. However, CNNs face two problems. First, they are computationally demanding, which makes their deployment…

Yu Guo, Axel Davy, Gabriele Facciolo, Jean-Michel Morel, Qiyu Jin

IEEE Signal Processing Letters - 2021

Informatique

Regularized bi-directional co-clustering

The simultaneous clustering of documents and words, known as co-clustering, has proved to be more effective than one-sided clustering in dealing with sparse high-dimensional datasets. By their nature, text data are also generally unbalanced and…

Séverine Affeldt, Lazhar Labiod, Mohamed Nadif

Statistics and Computing - 2021

Informatique

Regularized Dual-PPMI Co-clustering for Text Data

Co-clustering of document-term matrices has proved to be more effective than one-sided clustering. By their nature, text data are also generally unbalanced and directional. Recently, the von Mises-Fisher (vMF) mixture model was proposed to handle…

Séverine Affeldt, Lazhar Labiod, Mohamed Nadif

SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval - 2021

Sciences de l'ingénieur

A Refined Theory for Bending Vibratory Analysis of Thick Functionally Graded Beams

A refined beam theory that takes the thickness-stretching into account is presented in this study for the bending vibratory behavior analysis of thick functionally graded (FG) beams. In this theory, the number of unknowns is reduced to four instead…

Youssef Boutahar, Nadhir Lebaal, David Bassir

Mathematics - 2021

Topologie générale

ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results

This paper presents the computational challenge on differential geometry and topology that happened within the ICLR 2021 workshop "Geometric and Topological Representation Learning". The competition asked participants to provide creative…

Nina Miolane, Matteo Caorsi, Umberto Lupo, Marius Guerard, Nicolas Guigui, Johan Mathe, Yann Cabanes, Wojciech Reise, Thomas Davies, António Leitão, Somesh Mohapatra, Saiteja Utpala, Shailja Shailja, Gabriele Corso, Guoxi Liu, Federico Iuricich, Andrei Manolache, Mihaela Nistor, Matei Bejan, Armand Mihai Nicolicioiu, Bogdan-Alexandru Luchian, Mihai-Sorin Stupariu, Florent Michel, Khanh Dao Duc, Bilal Abdulrahman, Maxim Beketov, Elodie Maignant, Zhiyuan Liu, Marek Černý, Martin Bauw, Santiago Velasco-Forero, Jesus Angulo, Yanan Long

Sciences du Vivant

Cholinesterases in Tripartite Neuromuscular Synapse

The neuromuscular junction (NMJ) is a tripartite synapse in which not only presynaptic and post-synaptic cells participate in synaptic transmission, but also terminal Schwann cells (TSC). Acetylcholine (ACh) is the neurotransmitter that mediates the…

Konstantin Petrov, Svetlana Proskurina, Eric Krejci

Frontiers in Molecular Neuroscience - 2021

Modélisation et simulation

Extension of generic two-fluid VOF advection schemes to an arbitrary number of components

We propose a new and simple method to extend any two-fluid dimensionally split VOF schemes on Cartesian meshes to N-fluid problems in 2D and 3D. The method is symmetric by permutation of the fluids, so that it is independent of the ordering of…

Matthieu Ancellin, Bruno Després, Stéphane Jaouen

Statistiques

Apport du Transfer Learning pour la segmentation automatique de lésions cérébrales radio-induites chez des patients atteints de glioblastome à partir d’un nombre restreint d’IRMs annotées

Ces travaux sont issus du projet de recherche RAAI (Radiotherapy Assisted by AI, MIAI@Grenoble Alpes) dont l’objectif était de proposer un algorithme d’apprentissage automatique pour la segmentation d’hyper-intensités de la substance blanche à…

Thomas Coudert, Sophie Ancelet, Nadya Pyatigorskaya, Lucia Nichelli, Damien Ricard, Dimitri Psimaras, Marie Odile Bernier, Michel Dojat, Florence Forbes, Alan Tucholka

Journées de biostatistique 2021 du GDR « Statistiques & Santé » - 2021

Apprentissage

Transfer Learning methods for temporal data

Dans ce travail, nous proposons de nouvelles méthodes d'apprentissage par transfert pour l'analyse des séries temporelles. Motivés par des applications de désagrégation de la consommation d'électricité des ménages (NILM) et de surveillance de…

Guillaume Richard