'Inverse problems' diaporamas de présentation

Statistical Approaches to Inverse Problems

Statistical Approaches to Inverse Problems. DIIG seminars on inverse problems Insight and Algorithms Niels Bohr Institute Copenhagen, Denmark 27-29 May 2002 (Revised 13 May 2003) P.B. Stark Department of Statistics University of California Berkeley, CA 94720-3860

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Lecture 9 Inexact Theories

Lecture 9 Inexact Theories. Syllabus.

713 views • 66 slides

Lecture 1 Describing Inverse Problems

Lecture 1 Describing Inverse Problems. Syllabus.

1.06k views • 63 slides

MULTI-DISCIPLINARY ANALYSIS, INVERSE DESIGN AND OPTIMIZATION

MULTI-DISCIPLINARY ANALYSIS, INVERSE DESIGN AND OPTIMIZATION. George S. Dulikravich Professor and Director, MAIDO Institute Department of Mechanical and Aerospace Engineering The University of Texas at Arlington dulikra@mae.uta.edu ( Thanks to my students, postdocs and visiting scientists ).

769 views • 59 slides

Lecture 8 The Principle of Maximum Likelihood

Lecture 8 The Principle of Maximum Likelihood. Syllabus.

642 views • 55 slides

Sparse Representations of Signals: Theory and Applications *

660 views • 54 slides

Boundary-element methods in biological science and engineering

Boundary-element methods in biological science and engineering. Jaydeep P. Bardhan Dept. of Electrical and Computer Engineering Northeastern University, Boston MA. Four Points For Today. Cellular and molecular biomedical problems also need efficient simulation methods.

630 views • 50 slides

High Order Total Variation Minimization For Interior Computerized Tomography

High Order Total Variation Minimization For Interior Computerized Tomography. Jiansheng Yang School of Mathematical Sciences Peking University, P. R. China July 9, 2012. This is a joint work with Prof. Hengyong Yu, Prof. Ming Jiang,

690 views • 41 slides

Radiative Heat transfer and Applications for Glass Production Processes

563 views • 39 slides

Statistical Measures of Uncertainty in Inverse Problems

Statistical Measures of Uncertainty in Inverse Problems. Workshop on Uncertainty in Inverse Problems Institute for Mathematics and Its Applications Minneapolis, MN 19-26 April 2002 P.B. Stark Department of Statistics University of California Berkeley, CA 94720-3860

484 views • 37 slides

An introduction to Inverse Problems Ge193

An introduction to Inverse Problems Ge193. Malcolm Sambridge Research School of Earth Sciences Australian National University Malcolm.Sambridge@anu.edu.au Visiting Caltech (GPS) until mid December Room 252F malcolms@gps.caltech.edu. Course Contents. Characterizing inverse problems

650 views • 36 slides

Computational Challenges in Air Pollution Modelling

Computational Challenges in Air Pollution Modelling. Z. Zlatev National Environmental Research Institute 1. Why air pollution modelling? 2. Major physical and chemical processes 3. Need for splitting

425 views • 31 slides

Modern Seismology Lecture Outline

Modern Seismology Lecture Outline. Seismic networks and data centres Mathematical background for time series analysis Seismic processing, applications Filtering Correlation Instrument correction, Transfer functions Seismic inverse problems Hypocentre location Tomography. Key questions.

450 views • 30 slides

J. Daunizeau Brain and Spine Institute, Paris, France

J. Daunizeau Brain and Spine Institute, Paris, France Wellcome Trust Centre for Neuroimaging, London, UK. Bayesian inference. Overview of the talk. 1 Probabilistic modelling and representation of uncertainty 1.1 Bayesian paradigm 1.2 Hierarchical models

357 views • 26 slides

Graph problems

Graph problems. Partition: min cut Clustering bioinformatics Image segmentation VLSI placement Routing Linear arrangement: bandwidth, cutwidth Graph drawing low dimension embedding.

433 views • 25 slides

Inverse Problems Activities in China

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479 views • 19 slides

JMM Special Session

342 views • 15 slides

Intuitive vs. Computable Topological Aspects of Computational Electromagnetics

Intuitive vs. Computable Topological Aspects of Computational Electromagnetics. P. Robert Kotiuga prk@bu.edu Boston University.

249 views • 14 slides

Matrix Methods Summary

Matrix Methods Summary. Direct and Iterative Methods. Direct. Iterative - Slow. Iterative - Fast. Gaussian Elimination LU Decomposition Cholesky Method . Jacobi Gauss-Seidel Gauss-Seidel with SOR. Conjugate Gradient (sym) Bi-conjugate gradient GM-RES Multigrid .

225 views • 6 slides