330 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR67 papers
- Mathématiques Appliquées à Paris 5FR54 papers
- Sorbonne Paris CitéFR25 papers
- Université Paris CitéFR17 papers
- Délégation Paris 5FR9 papers
- Laboratoire Psychologie de la PerceptionFR9 papers
- Sorbonne UniversitéFR9 papers
- Université Paris DiderotFR9 papers
- InsermFR8 papers
- Université Pierre-et-Marie-CurieFR8 papers
- École Normale Supérieure - PSLFR7 papers
- Université Paris NanterreFR7 papers
122 papers
Coconut: sortable summarizations for scalable indexes over static and streaming data series
Haridimos Kondylakis, Niv Dayan, Kostas Zoumpatianos +1
Many modern applications produce massive streams of data series that need to be analyzed, requiring efficient similarity search operations. However, the state-of-the-art data serie…
Understanding and monitoring the evolution of the Covid-19 epidemic from medical emergency calls: the example of the Paris area
Stéphane Gaubert, Marianne Akian, Xavier Allamigeon +16
We portray the evolution of the Covid-19 epidemic during the crisis of March-April 2020 in the Paris area, by analyzing the medical emergency calls received by the EMS of the four…
Fredholm theory for the mean first-passage time of integrate-and-fire oscillators with colored noise input
Carl van Vreeswijk, Farzad Farkhooi
We develop a method to investigate the effect of noise timescales on the first-passage time of nonlinear oscillators. Using Fredholm theory, we derive an exact integral equation fo…
Stationary characters on lattices of semisimple Lie groups
Rémi Boutonnet, Cyril Houdayer
We show that stationary characters on irreducible lattices of higher-rank connected semisimple Lie groups are conjugation invariant, that is, they are genuine characters. Th…
Knowledge transfer in deep block-modular neural networks
Alexander V. Terekhov, Guglielmo Montone, J. Kevin O'Regan
Although deep neural networks (DNNs) have demonstrated impressive results during the last decade, they remain highly specialized tools, which are trained -- often from scratch -- t…
Learning abstract perceptual notions: the example of space
Alexander V. Terekhov, J. Kevin O'Regan
Humans are extremely swift learners. We are able to grasp highly abstract notions, whether they come from art perception or pure mathematics. Current machine learning techniques de…
Systematics of consistent truncations from generalised geometry
Davide Cassani, Gregoire Josse, Michela Petrini +1
We present a generalised geometry framework for systematically constructing consistent truncations of ten- and eleven-dimensional supergravity preserving varying fractions of super…
Mechanical characterization of cells and microspheres sorted by acoustophoresis with in-line resistive pulse sensing
Antoine Riaud, Anh L. P. Thai, Wei Wang +1
Resistive Pulse Sensing (RPS) is a key label-free technology to measure particles and single-cell size distribution. As a growing corpus of evidence supports that cancer cells exhi…
DVDnet: A Fast Network for Deep Video Denoising
Matias Tassano, Julie Delon, Thomas Veit
In this paper, we propose a state-of-the-art video denoising algorithm based on a convolutional neural network architecture. Previous neural network based approaches to video denoi…
Morphological organization of point-to-point transport in complex networks
Min-Yeong Kang, Geoffroy Berthelot, Liubov Tupikina +4
We investigate the structural organization of the point-to-point electric, diffusive or hydraulic transport in complex scale-free networks. The random choice of two nodes, a source…
End-to-End Entity Resolution for Big Data: A Survey
Vassilis Christophides, Vasilis Efthymiou, Themis Palpanas +2
One of the most important tasks for improving data quality and the reliability of data analytics results is Entity Resolution (ER). ER aims to identify different descriptions that…
A system of interacting neurons with short term synaptic facilitation
Antonio Galves, Eva Löcherbach, Christophe Pouzat +1
In this paper we present a simple microscopic stochastic model describing short term plasticity within a large homogeneous network of interacting neurons. Each neuron is represente…
Bandwidth Selection for the Wolverton-Wagner Estimator
Fabienne Comte, Nicolas Marie
For independent random variables having the same Hölder continuous density, this paper deals with controls of the Wolverton-Wagner's estimator MSE and MISE. Then, for a bandwid…
Regression modelling of interval censored data based on the adaptive ridge procedure
Olivier Bouaziz, Eva Lauridsen, Grégory Nuel
A new method for the analysis of time to ankylosis complication on a dataset of replanted teeth is proposed. In this context of left-censored, interval-censored and right-censored…
Structural and temporal heterogeneities on networks
Liubov Tupikina, Denis S. Grebenkov
A heterogeneous continuous time random walk is an analytical formalism for studying and modeling diffusion processes in heterogeneous structures on microscopic and macroscopic scal…
Recent advances in methodology for clinical trials in small populations: the InSPiRe project
T. Friede, M. Posch, S. Zohar +19
Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This l…
MGP: Un algorithme de planification temps réel prenant en compte l'évolution dynamique du but
Damien Pellier, Mickaël Vanneufville, Humbert Fiorino +2
Devising intelligent robots or agents that interact with humans is a major challenge for artificial intelligence. In such contexts, agents must constantly adapt their decisions acc…
Planification en temps réel avec agenda de buts et sauts
Damien Pellier, Bruno Bouzy, Marc Métivier
In the context of real-time planning, this paper investigates the contributions of two enhancements for selecting actions. First, the agenda-driven planning enhancement ranks relev…
Hedging Algorithms and Repeated Matrix Games
Bruno Bouzy, Marc Métivier, Damien Pellier
Playing repeated matrix games (RMG) while maximizing the cumulative returns is a basic method to evaluate multi-agent learning (MAL) algorithms. Previous work has shown that ,…
Learning agent's spatial configuration from sensorimotor invariants
Alban Laflaquière, J. Kevin O'Regan, Sylvain Argentieri +2
The design of robotic systems is largely dictated by our purely human intuition about how we perceive the world. This intuition has been proven incorrect with regard to a number of…
Learning an internal representation of the end-effector configuration space
Alban Laflaquière, Alexander V. Terekhov, Bruno Gas +1
Current machine learning techniques proposed to automatically discover a robot kinematics usually rely on a priori information about the robot's structure, sensors properties or en…
Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?
Marcela Carvalho, Bertrand Le Saux, Pauline Trouvé-Peloux +2
Depth estimation is of critical interest for scene understanding and accurate 3D reconstruction. Most recent approaches in depth estimation with deep learning exploit geometrical s…
On A Mixture Of Brenier and Strassen Theorems
Nathael Gozlan, Nicolas Juillet
We give a characterization of optimal transport plans for a variant of the usual quadratic transport cost introduced in [33]. Optimal plans are composition of a deterministic trans…
Crawling migration under chemical signalling: a stochastic particle model
Christèle Etchegaray, Nicolas Meunier
Cell migration is a fundamental process involved in physiological phenomena such as the immune response and morphogenesis, but also in pathological processes, such as the developme…