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A systematic approach to model validation based on Bayesian updates and prediction related rejection criteria

Publications associées (67)

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Saddlepoint approximation for mixture models

Anthony Christopher Davison

Two-component mixture distributions with one component a point mass and the other a continuous density may be used as priors for Bayesian inference when sparse representation of an underlying signal is required. We show how saddlepoint approximation in suc ...

2009

Compressed sensing for radio interferometry: prior-enhanced Basis Pursuit imaging techniques

Pierre Vandergheynst, Yves Wiaux, Gilles Puy, Laurent Jacques

We propose and assess the performance of new imaging techniques for radio interferometry that rely on the versatility of the compressed sensing framework to account for prior information on the signals. The present manuscript represents a summary of recent ...

2009

Bayesian Inference and Optimal Design in the Sparse Linear Model

Matthias Seeger

The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maximum a posteriori sparse solutions and neglect to represent posterior uncertain ...

Massachusetts Institute of Technology Press2008

Bayesian Inference for Spiking Neuron Models with a Sparsity Prior

Matthias Seeger, Matthias Bethge

Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the expectation propagation algorithm, we are able to approximate the full poster ...

2008

SHAPE PRIOR BASED ON STATISTICAL MAP FOR ACTIVE CONTOUR SEGMENTATION

Jean-Philippe Thiran, Valérie Duay, Alia Lemkaddem, Nawal Houhou

We propose a new method for performing active contour segmentation based on the statistical prior knowledge of the object to detect. From a binary training set of objects, a statistical map describes the possible shapes of the object by computing the proba ...

2008

Out-of-body experiences: false climbs in a supine position?

Olaf Blanke

Out-of-body experiences (OBEs) are illusions, where people experience themselves as being located outside their physical body and often flying or floating at an elevated location. Here, we propose that the flying and floating in OBEs can be explained as th ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008

The Boolean Solution to the Congested IP Link Location Problem: Theory and Practice

Patrick Thiran, Xuan Hung Nguyen

Like other problems in network tomography or traffic matrix estimation, the location of congested IP links from end-to-end measurements requires solving a system of equations that relate the measurement outcomes with the variables representing the status o ...

2007

Bayesian Approach for Indoor Pedestrian Localisation

The principal concept of navigation is to start from a known (initial) position and to ensure a continued and reliable localisation of the user during his/her movement. The initial position of the trajectory is usually obtained via GPS or defined by the us ...

STRC 20062006

Bayesian Approach for Indoor Pedestrian Localisation

Michel Bierlaire, Bertrand Merminod

2006

Map-matching for pedestrians via Bayesian inference

Michel Bierlaire, Bertrand Merminod

A navigation process is to start from a known (initial) position and to ensure a continued localisation of the user during the movement. Consider a pedestrian navigation system which contains a GPS receiver and a set of inertial sensors connected with the ...

2006