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vestrela@id.uff.brProfessor
Universidade Federal Fluminense
vestrela@id.uff.br
B.Sc. degree from Federal University of Rio de Janeiro (UFRJ) in Electrical and Computer Engineering (ECE); M.Sc. from the Instituto Tecnológico de Aeronáutica (ITA), Sao Jose ...
SIAMSC
2011
219views more  SIAMSC 2011»
7 years 10 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
CORR
2011
Springer
235views Education» more  CORR 2011»
7 years 10 months ago
On the accuracy of language trees
Historical linguistics aims at inferring the most likely language phylogenetic tree starting from information concerning the evolutionary relatedness of languages. The available i...
Simone Pompei, Vittorio Loreto, Francesca Tria
SIGPRO
2010
154views more  SIGPRO 2010»
8 years 1 months ago
UPRE method for total variation parameter selection
Total Variation (TV) regularization is a popular method for solving a wide variety of inverse problems in image processing. In order to optimize the reconstructed image, it is imp...
Youzuo Lin, Brendt Wohlberg, Hongbin Guo
SIAMSC
2010
159views more  SIAMSC 2010»
8 years 1 months ago
Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems
A greedy algorithm for the construction of a reduced model with reduction in both parameter and state is developed for efficient solution of statistical inverse problems governed b...
Chad Lieberman, Karen Willcox, Omar Ghattas
TIP
1998
142views more  TIP 1998»
8 years 2 months ago
Inversion of large-support ill-posed linear operators using a piecewise Gaussian MRF
Abstract—We propose a method for the reconstruction of signals and images observed partially through a linear operator with a large support (e.g., a Fourier transform on a sparse...
Mila Nikolova, Jérôme Idier, Ali Moha...
JAT
2008
100views more  JAT 2008»
8 years 3 months ago
Direct and inverse results in variable Hilbert scales
Variable Hilbert scales are an important tool for the recent analysis of inverse problems in Hilbert spaces, as these constitute a way to describe smoothness of objects other than ...
Peter Mathé, Bernd Hofmann
CORR
2010
Springer
171views Education» more  CORR 2010»
8 years 3 months ago
Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity
A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP...
Guoshen Yu, Guillermo Sapiro, Stéphane Mall...
METMBS
2003
138views Mathematics» more  METMBS 2003»
8 years 4 months ago
A Stochastic Method for Solving Inverse Problems in Epidemic Modelling
— We describe a stochastic optimization method that can be used to solve inverse problems in epidemic modelling. Although in general it cannot be expected that these inverse prob...
Dominik Novotni, Andreas Weber 0004
SC
2005
ACM
8 years 8 months ago
Dynamic Data-Driven Inversion For Terascale Simulations: Real-Time Identification Of Airborne Contaminants
In contrast to traditional terascale simulations that have known, fixed data inputs, dynamic data-driven (DDD) applications are characterized by unknown data and informed by dynam...
Volkan Akcelik, George Biros, Andrei Draganescu, J...
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