Publications related to Dirichlet distribution

Intensity and phase fields behind Phase Shifting Masks studied with High Resolution Interference Microscopy

Hans Peter Herzig, Toralf Scharf, Krishnaparvathy Puthankovilakam

The proximity printing industry is in real need of high resolution results and it can be done using Phase Shift Mask (PSM) or by applying Optical Proximity Correction (OPC). In our research we are trying to find out details of how light fields behind the s ...

Spie-Int Soc Optical Engineering2015

A new formulation for imposing Dirichlet boundary conditions on non-matching meshes

Jean-François Molinari, Alejandro Marcos Aragon, Aurelia Isabel Cuba Ramos

Generating matching meshes for problems with complex boundaries is often an intricate process, and the use of non-matching meshes appears as an appealing solution. Yet, enforcing boundary conditions on non-matching meshes is not a straightforward process, ...

Wiley-Blackwell2015

Temporal Analysis of Motif Mixtures using Dirichlet Processes

Jean-Marc Odobez, Rémi Emonet, Jagannadan Varadarajan

In this article, we present a new model for unsupervised discovery of recurrent temporal patterns (or motifs) in time series (or documents). The model is designed to handle the difficult case of multivariate time series obtained from a mixture of activitie ...

2014

A Statistical Approach To The Inverse Problem In Magnetoencephalography

Zhigang Yao

Magnetoencephalography (MEG) is an imaging technique used to measure the magnetic field outside the human head produced by the electrical activity inside the brain. The MEG inverse problem, identifying the location of the electrical sources from the magnet ...

Inst Mathematical Statistics2014

Mass distributions marginalized over per-event errors

Frédéric Guillaume Dupertuis

We present generalizations of the Crystal Ball function to describe mass peaks in which the per event mass resolution is unknown and marginalized over. The presented probability density functions are tested using a series of toy Monte Carlo samples generat ...

Elsevier Science Bv2014

Efficient inference for spatial extreme value processes associated to log-Gaussian random functions

Jonathan A. Tawn, Jennifer Lynne Wadsworth

Max-stable processes arise as the only possible nontrivial limits for maxima of affinely normalized identically distributed stochastic processes, and thus form an important class of models for the extreme values of spatial processes. Until recently, infere ...

Oxford University Press2014

Statistical models for HMM/ANN hybrids

Philip Neil Garner, David Imseng

We present a theoretical investigation into the use of normalised artificial neural network (ANN) outputs in the context of hidden Markov models (HMMs). The work is motivated by the pursuit of a more theoretically rigorous understanding of the Kullback-Lie ...

Idiap2013

ABC Reinforcement Learning

Christos Dimitrakakis, Nikolaos Tziortziotis

This paper introduces a simple, general framework for likelihood-free Bayesian reinforcement learning, through Approximate Bayesian Computation (ABC). The main advantage is that we only require a prior distribution on a class of simulators (generative mode ...

2013

Continuous Localization Using Sparsity Constraints for High-Density Super-Resolution Microscopy

Michaël Unser, Cédric René Jean Vonesch, Hagay Kirshner

Super-resolution localization microscopy relies on sparse activation of photo-switchable probes. Such activation, however, introduces limited temporal resolution. High-density imaging overcomes this limitation by allowing several neighboring probes to be a ...

IEEE2013

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Dirichlet distribution

Intensity and phase fields behind Phase Shifting Masks studied with High Resolution Interference Microscopy

A new formulation for imposing Dirichlet boundary conditions on non-matching meshes

Temporal Analysis of Motif Mixtures using Dirichlet Processes

A Statistical Approach To The Inverse Problem In Magnetoencephalography

Mass distributions marginalized over per-event errors

Efficient inference for spatial extreme value processes associated to log-Gaussian random functions

Statistical models for HMM/ANN hybrids

ABC Reinforcement Learning

Continuous Localization Using Sparsity Constraints for High-Density Super-Resolution Microscopy

MATHICSE Technical Report : Analytic regularity and collocation approximation for PDEs with random domain deformations

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Chat with Graph Search

MATHICSE Technical Report : Analytic regularity and collocation approximation for PDEs with random domain deformations

A Statistical Approach To The Inverse Problem In Magnetoencephalography

Efficient inference for spatial extreme value processes associated to log-Gaussian random functions

Temporal Analysis of Motif Mixtures using Dirichlet Processes

ABC Reinforcement Learning

Intensity and phase fields behind Phase Shifting Masks studied with High Resolution Interference Microscopy

Statistical models for HMM/ANN hybrids

Continuous Localization Using Sparsity Constraints for High-Density Super-Resolution Microscopy

Mass distributions marginalized over per-event errors

A new formulation for imposing Dirichlet boundary conditions on non-matching meshes