180 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université Paris-SaclayFR185 papers
- Centre National de la Recherche ScientifiqueFR119 papers
- Institut national de recherche en sciences et technologies du numériqueFR29 papers
- Laboratoire Interdisciplinaire de PhysiqueFR26 papers
- Sorbonne UniversitéFR20 papers
- Centre Inria de SaclayFR17 papers
- CentraleSupélecFR15 papers
- Local Initiatives Support CorporationUS15 papers
- Université Paris CitéFR15 papers
- Universidad Complutense de MadridES14 papers
- École Normale Supérieure - PSLFR11 papers
- Gleason (United States)US10 papers
50 papers · 1 filter
Cosmology with cosmic web environments II. Redshift-space auto and cross power spectra
Tony Bonnaire, Joseph Kuruvilla, Nabila Aghanim +1
Degeneracies among parameters of the cosmological model are known to drastically limit the information contained in the matter distribution. In the first paper of this series, we s…
Technological taxonomies for hypernym and hyponym retrieval in patent texts
You Zuo, Yixuan Li, Alma Parias García +1
This paper presents an automatic approach to creating taxonomies of technical terms based on the Cooperative Patent Classification (CPC). The resulting taxonomy contains about 170k…
The -weak order and -permutahedra I: combinatorics and lattice structure
Cesar Ceballos, Viviane Pons
This is the first contribution of a sequence of papers introducing the notions of -weak order and -permutahedra, certain discrete objects that are indexed by a sequence of no…
Continuous Methods : Adaptively intrusive reduced order model closure
Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi +4
Reduced order modeling methods are often used as a mean to reduce simulation costs in industrial applications. Despite their computational advantages, reduced order models (ROMs) o…
DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations)
Matthieu Nastorg, Marc Schoenauer, Guillaume Charpiat +3
This paper proposes a novel Machine Learning-based approach to solve a Poisson problem with mixed boundary conditions. Leveraging Graph Neural Networks, we develop a model able to…
Knowledge Graph Refinement based on Triplet BERT-Networks
Armita Khajeh Nassiri, Nathalie Pernelle, Fatiha Sais +1
Knowledge graph embedding techniques are widely used for knowledge graph refinement tasks such as graph completion and triple classification. These techniques aim at embedding the…
Graph Neural Network-based Surrogate Models for Finite Element Analysis
Meduri Venkata Shivaditya, José Alves, Francesca Bugiotti +1
Current simulation of metal forging processes use advanced finite element methods. Such methods consist of solving mathematical equations, which takes a significant amount of time…
Weakly-supervised Fingerspelling Recognition in British Sign Language Videos
K R Prajwal, Hannah Bull, Liliane Momeni +3
The goal of this work is to detect and recognize sequences of letters signed using fingerspelling in British Sign Language (BSL). Previous fingerspelling recognition methods have n…
Thermodynamics of bidirectional associative memories
Adriano Barra, Giovanni Catania, Aurélien Decelle +1
In this paper we investigate the equilibrium properties of bidirectional associative memories (BAMs). Introduced by Kosko in 1988 as a generalization of the Hopfield model to a bip…
Acyclic colourings of graphs with obstructions
Quentin Chuet, Johanne Cohen, François Pirot
Given a graph , a colouring of is \emph{acyclic} if it is a proper colouring of and every cycle contains at least three colours. Its acyclic chromatic number is…
Short-range and long-range order: a transition in block-gluing behavior in Hom shifts
Silvere Gangloff, Benjamin Hellouin de Menibus, Piotr Oprocha
Hom shifts form a class of multidimensional shifts of finite type (SFT) and consist of colorings of the grid Z2 where adjacent colours must be neighbors in a fixed finite undirecte…
Free Dynamics of Feature Learning Processes
Cyril Furtlehner
Regression models usually tend to recover a noisy signal in the form of a combination of regressors, also called features in machine learning, themselves being the result of a lear…
Natural Language Processing for Cognitive Analysis of Emotions
Gustave Cortal, Alain Finkel, Patrick Paroubek +1
Emotion analysis in texts suffers from two major limitations: annotated gold-standard corpora are mostly small and homogeneous, and emotion identification is often simplified as a…
Impact of droplets onto surfactant-laden thin liquid films
C. R. Constante-Amores, L. Kahouadji, S. Shin +5
We study the effect of insoluble surfactants on the impact of surfactant-free droplets on surfactant-laden thin liquid films via a fully three-dimensional direct numerical simulati…
Scalability in Visualization
Gaëlle Richer, Alexis Pister, Moataz Abdelaal +3
We introduce a conceptual model for scalability designed for visualization research. With this model, we systematically analyze over 120 visualization publications from 1990-2020 t…
Self-stabilization and byzantine tolerance for maximal independent
Johanne Cohen, Laurence Pilard, François Pirot +1
We analyze the impact of transient and Byzantine faults on the construction of a maximal independent set in a general network. We adapt the self-stabilizing algorithm presented by…
NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results
Dustin Carrión-Ojeda, Hong Chen, Adrian El Baz +6
We present the design and baseline results for a new challenge in the ChaLearn meta-learning series, accepted at NeurIPS'22, focusing on "cross-domain" meta-learning. Meta-learning…
Reynolds Stress Anisotropy Tensor Predictions for Turbulent Channel Flow using Neural Networks
Jiayi Cai, Pierre-Emmanuel Angeli, Jean-Marc Martinez +2
The Reynolds-Averaged Navier-Stokes (RANS) approach remains a backbone for turbulence modeling due to its high cost-effectiveness. Its accuracy is largely based on a reliable Reyno…
Memory and rejuvenation in spin glasses: aging systems are ruled by more than one length scale
Janus Collaboration, M. Baity-Jesi, E. Calore +22
Memory and rejuvenation effects in the magnetic response of off-equilibrium spin glasses have been widely regarded as the doorway into the experimental exploration of ultrametricit…
xMLC -- A Toolkit for Machine Learning Control
Guy Y. Cornejo Maceda, François Lusseyran, Bernd R. Noack
xMLC is the second book of this `Machine Learning Tools in Fluid Mechanics' Series and focuses on Machine Learning Control (MLC). The objectives of this book are two-fold: First, p…
Meta-learning from Learning Curves Challenge: Lessons learned from the First Round and Design of the Second Round
Manh Hung Nguyen, Lisheng Sun, Nathan Grinsztajn +1
Meta-learning from learning curves is an important yet often neglected research area in the Machine Learning community. We introduce a series of Reinforcement Learning-based meta-l…
Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design
Gaëtan Serré, Eva Boguslawski, Benjamin Donnot +3
Current rapid changes in climate increase the urgency to change energy production and consumption management, to reduce carbon and other green-house gas production. In this context…
Ternary and Quaternary CNTFET Full Adders are less efficient than the Binary Ones for Carry-Propagate Adders
Daniel Etiemble
In Carry Propagate Adders, carry propagation is the critical delay. The most efficient scheme is to generate Cout0 (Cin=0) and Cout1(Cin=1) and multiplex the correct output accordi…
Continuous Methods : Hamiltonian Domain Translation
Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi +2
This paper proposes a novel approach to domain translation. Leveraging established parallels between generative models and dynamical systems, we propose a reformulation of the Cycl…