129 citations · 138 across the 12 of their papers we have counts for
6 papers · 1 filter
Off-the-grid prediction and testing for linear combination of translated features
Cristina Butucea, Jean-François Delmas, Anne Dutfoy +1
We consider a model where a signal (discrete or continuous) is observed with an additive Gaussian noise process. The signal is issued from a linear combination of a finite but incr…
Simultaneous off-the-grid learning of mixtures issued from a continuous dictionary
Cristina Butucea, Jean-François Delmas, Anne Dutfoy +1
In this paper we observe a set, possibly a continuum, of signals corrupted by noise. Each signal is a finite mixture of an unknown number of features belonging to a continuous dict…
Adaptive importance sampling based on fault tree analysis for piecewise deterministic Markov process
Guillaume Chennetier, Hassane Chraibi, Anne Dutfoy +1
Piecewise deterministic Markov processes (PDMPs) can be used to model complex dynamical industrial systems. The counterpart of this modeling capability is their simulation cost, wh…
Reparameterization of extreme value framework for improved Bayesian workflow
Théo Moins, Julyan Arbel, Stéphane Girard +1
Using Bayesian methods for extreme value analysis offers an alternative to frequentist ones, with several advantages such as easily dealing with parametric uncertainty or studying…
Off-the-grid learning of mixtures from a continuous dictionary
Cristina Butucea, Jean-François Delmas, Anne Dutfoy +1
We consider a general non-linear model where the signal is a finite mixture of an unknown, possibly increasing, number of features issued from a continuous dictionary parameterized…
On the use of a local to improve MCMC convergence diagnostic
Théo Moins, Julyan Arbel, Anne Dutfoy +1
Diagnosing convergence of Markov chain Monte Carlo is crucial and remains an essentially unsolved problem. Among the most popular methods, the potential scale reduction factor, com…