298 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université de LilleFR364 papers
- Centre National de la Recherche ScientifiqueFR257 papers
- École Centrale de LilleFR212 papers
- Centre de Recherche en InformatiqueFR203 papers
- Université Paris-SaclayFR74 papers
- Institut d'Astrophysique SpatialeFR64 papers
- Sorbonne UniversitéFR59 papers
- Institut de Recherche en Astrophysique et PlanétologieFR58 papers
- Université Paris CitéFR57 papers
- Université Paris Sciences et LettresFR53 papers
- Ludwig-Maximilians-Universität MünchenDE52 papers
- CEA Paris-SaclayFR51 papers
17 papers · 1 filter
Bayesian anti-sparse coding
Clément Elvira, Pierre Chainais, Nicolas Dobigeon
Sparse representations have proven their efficiency in solving a wide class of inverse problems encountered in signal and image processing. Conversely, enforcing the information to…
Density estimation on the rotation group using diffusive wavelets
Nicolas Le Bihan, Julien Flamant, Jonathan H. Manton
This paper considers the problem of estimating probability density functions on the rotation group . Two distinct approaches are proposed, one based on characteristic functi…
Provenance Circuits for Trees and Treelike Instances (Extended Version)
Antoine Amarilli, Pierre Bourhis, Pierre Senellart
Query evaluation in monadic second-order logic (MSO) is tractable on trees and treelike instances, even though it is hard for arbitrary instances. This tractability result has been…
Shape Expressions Schemas
Iovka Boneva, Jose E. Labra Gayo, Eric G. Prud'hommeaux +1
We present Shape Expressions (ShEx), an expressive schema language for RDF designed to provide a high-level, user friendly syntax with intuitive semantics. ShEx allows to describe…
Generalized Multiple Importance Sampling
Víctor Elvira, Luca Martino, David Luengo +1
Importance Sampling methods are broadly used to approximate posterior distributions or some of their moments. In its standard approach, samples are drawn from a single proposal dis…
Operator-valued Kernels for Learning from Functional Response Data
Hachem Kadri, Emmanuel Duflos, Philippe Preux +3
In this paper we consider the problems of supervised classification and regression in the case where attributes and labels are functions: a data is represented by a set of function…
A Bayesian Compressed Sensing Kalman Filter for Direction of Arrival Estimation
Matthew Hawes, Lyudmila Mihaylova, Francois Septier +1
In this paper, we look to address the problem of estimating the dynamic direction of arrival (DOA) of a narrowband signal impinging on a sensor array from the far field. The initia…
DeltaImpactFinder: Assessing Semantic Merge Conflicts with Dependency Analysis
Martín Dias, Guillermo Polito, Damien Cassou +1
In software development, version control systems (VCS) provide branching and merging support tools. Such tools are popular among developers to concurrently change a code-base in se…
Adapting the Number of Particles in Sequential Monte Carlo Methods through an Online Scheme for Convergence Assessment
Víctor Elvira, Joaquín Míguez, Petar M. Djurić
Particle filters are broadly used to approximate posterior distributions of hidden states in state-space models by means of sets of weighted particles. While the convergence of the…
How Can Subsampling Reduce Complexity in Sequential MCMC Methods and Deal with Big Data in Target Tracking?
Allan De Freitas, François Septier, Lyudmila Mihaylova +1
Target tracking faces the challenge in coping with large volumes of data which requires efficient methods for real time applications. The complexity considered in this paper is whe…
Inference for determinantal point processes without spectral knowledge
Rémi Bardenet, Michalis K. Titsias
Determinantal point processes (DPPs) are point process models that naturally encode diversity between the points of a given realization, through a positive definite kernel . DPP…
A Bayesian fusion model for space-time reconstruction of finely resolved velocities in turbulent flows from low resolution measurements
Linh Van Nguyen, Jean-Philippe Laval, Pierre Chainais
The study of turbulent flows calls for measurements with high resolution both in space and in time. We propose a new approach to reconstruct High-Temporal-High-Spatial resolution v…
Gauge Invariant Framework for Shape Analysis of Surfaces
Alice Barbara Tumpach, Hassen Drira, Mohamed Daoudi +1
This paper describes a novel framework for computing geodesic paths in shape spaces of spherical surfaces under an elastic Riemannian metric. The novelty lies in defining this Riem…
On Markov chain Monte Carlo methods for tall data
Rémi Bardenet, Arnaud Doucet, Chris Holmes
Markov chain Monte Carlo methods are often deemed too computationally intensive to be of any practical use for big data applications, and in particular for inference on datasets co…
SMC-ABC methods for the estimation of stochastic simulation models of the limit order book
Gareth W. Peters, Efstathios Panayi, Francois Septier
In this paper we consider classes of models that have been recently developed for quantitative finance that involve modelling a highly complex multivariate, multi-attribute stochas…
Langevin and Hamiltonian based Sequential MCMC for Efficient Bayesian Filtering in High-dimensional Spaces
Francois Septier, Gareth W. Peters
Nonlinear non-Gaussian state-space models arise in numerous applications in statistics and signal processing. In this context, one of the most successful and popular approximation…
Casper: Debugging Null Dereferences with Dynamic Causality Traces
Benoit Cornu, Earl T. Barr, Lionel Seinturier +1
Fixing a software error requires understanding its root cause. In this paper, we introduce ''causality traces'', crafted execution traces augmented with the information needed to r…