Publication

Variational Bayesian Inference Techniques

Publications associées (53)

Probabilistic Depth Image Registration incorporating Nonvisual Information

In this paper, we derive a probabilistic registration algorithm for object modeling and tracking. In many robotics applications, such as manipulation tasks, nonvisual information about the movement of the object is available, which we will combine with the ...

Ieee2012

Bayesian inference from composite likelihoods, with an application to spatial extremes

Anthony Christopher Davison

Composite likelihoods are increasingly used in applications where the full likelihood is analytically unknown or computationally prohibitive. Although some frequentist properties of the maximum composite likelihood estimator are akin to those of the maximu ...

Academia Sinica, Institute of Statistical Science2012

Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models

Matthias Seeger

Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or super-resolution, can be addressed by maximizing the posterior distribution of a sparse linear model (SLM). We show how higher- ...

2011

A New Hybrid Bayesian-Variational Particle Filter With Application To Mitotic Cell Tracking

Michaël Unser, Ricard Delgado Gonzalo

Tracking algorithms are traditionally based on either a variational approach or a Bayesian one. In the variational case, a cost function is established between two consecutive frames and minimized by standard optimization algorithms. In the Bayesian case, ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

A New Hybrid Bayesian-Variational Particle Filter with Application to Mitotic Cell Tracking

Michaël Unser, Ricard Delgado Gonzalo

IEEE2011

Posterior Features for Template-based ASR

Hervé Bourlard, Joel Praveen Pinto, Serena Soldo

This paper investigates the use of phoneme class conditional probabilities as features (posterior features) for template-based ASR. Using 75 words and 600 words task-independent and speaker-independent setup on Phonebook database, we investigate the use of ...

2011

Preference elicitation and inverse reinforcement learning

Christos Dimitrakakis

We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous work on Bayesian inverse reinforcement learning and allows us to obtain a pos ...

2011

Context models on sequences of covers

Christos Dimitrakakis

We present a class of models that, via a simple construction, enables exact, incremental, non-parametric, polynomial-time, Bayesian inference of conditional measures. The approach relies upon creating a sequence of covers on the conditioning variable and m ...

2011

Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference

Matthias Seeger

We propose a novel algorithm to solve the expectation propagation relaxation of Bayesian inference for continuous-variable graphical models. In contrast to most previous algorithms, our method is provably convergent. By marrying convergent EP ideas from (O ...

2011

Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

Jean-Philippe Thiran, Meritxell Bach Cuadra, Subrahmanyam Venkata Ravi Mohana Sai Gorthi

This paper presents 3-D brain tissue classification schemes using three recent promising energy minimization methods for Markov random fields: graph cuts, loopy belief propagation and tree-reweighted message passing. The classification is performed using t ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

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