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July 24, 2019, at 09:45 PM by 147.142.143.249 -
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[[Mod412_2015 | Module 412 in 2015]], [[BUC5 | BUC5 compute resources]], , [[Blockkurs |Blockkurs on Markov Chain Monte Carlo for Inverse Problems in PDEs]]
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[[Mod412_2015 | Module 412 in 2015]], [[BUC5 | BUC5 compute resources]], [[Blockkurs |Blockkurs on Markov Chain Monte Carlo for Inverse Problems in PDEs]]
July 24, 2019, at 09:44 PM by 147.142.143.249 -
Changed line 53 from:
[[Mod412_2015 | Module 412 in 2015]], [[BUC5 | BUC5 compute resources]]
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[[Mod412_2015 | Module 412 in 2015]], [[BUC5 | BUC5 compute resources]], , [[Blockkurs |Blockkurs on Markov Chain Monte Carlo for Inverse Problems in PDEs]]
September 21, 2016, at 05:36 PM by 109.145.36.112 -
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[[Mod412_2015 | Module 412 in 2015]]
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[[Mod412_2015 | Module 412 in 2015]], [[BUC5 | BUC5 compute resources]]
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*''Project:''
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 *Image of good and bad cells in Matlab mat format [[Attach:slide.mat | slide.mat]], or as [[slide.tif|slide.tif]]. Matlab code [[Attach:makefake.m | makefake.m]] that generated the image, and uses functions [[Attach:putgood.m | putgood.m]] and [[Attach:putbad.m | putbad.m]].
to:
 *Image of good and bad cells in Matlab mat format [[Attach:slide.mat | slide.mat]], or as [[Attach:slide.tif|slide.tif]]. Matlab code [[Attach:makefake.m | makefake.m]] that generated the image, and uses functions [[Attach:putgood.m | putgood.m]] and [[Attach:putbad.m | putbad.m]].
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 *Image of good and bad cells in Matlab mat format [[Attach:slide.mat | slide.mat]], or as [[https://coursesupport.physics.otago.ac.nz/wiki/pmwiki.php/ELEC445/HomePage?action=download&upname=slide.tif|slide.tif]]. Matlab code [[Attach:makefake.m | makefake.m]] that generated the image, and uses functions [[Attach:putgood.m | putgood.m]] and [[Attach:putbad.m | putbad.m]].
to:
 *Image of good and bad cells in Matlab mat format [[Attach:slide.mat | slide.mat]], or as [[slide.tif|slide.tif]]. Matlab code [[Attach:makefake.m | makefake.m]] that generated the image, and uses functions [[Attach:putgood.m | putgood.m]] and [[Attach:putbad.m | putbad.m]].
Changed line 47 from:
 *Image of good and bad cells in Matlab mat format [[Attach:slide.mat | slide.mat]], or as [[Attach:slide.tif | slide.tif]]. Matlab code [[Attach:makefake.m | makefake.m]] that generated the image, and uses functions [[Attach:putgood.m | putgood.m]] and [[Attach:putbad.m | putbad.m]].
to:
 *Image of good and bad cells in Matlab mat format [[Attach:slide.mat | slide.mat]], or as [[https://coursesupport.physics.otago.ac.nz/wiki/pmwiki.php/ELEC445/HomePage?action=download&upname=slide.tif|slide.tif]]. Matlab code [[Attach:makefake.m | makefake.m]] that generated the image, and uses functions [[Attach:putgood.m | putgood.m]] and [[Attach:putbad.m | putbad.m]].
August 24, 2016, at 09:20 AM by 139.80.236.40 -
Changed line 34 from:
 *Paper on MCMC using an approximation, ADAMH
to:
 *[[Attach:ChristenFox2005.pdf | Paper on MCMC using an approximation]], ADAMH
August 15, 2016, at 09:26 AM by 139.80.236.40 -
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 *Attach:Paper on MTO for image deblurring
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 *[[Attach:MTC.pdf | Paper on MTC for image deblurring ]]
August 15, 2016, at 09:26 AM by 139.80.236.40 -
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 *Paper on MTO for image deblurring
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 *Attach:Paper on MTO for image deblurring
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 * Useful code snippets: [[Attach:tauvsd.m | tauvsd.m]] (an example of running AM on multivariate normals), [[Attach:stdnorm_example.m | stdnorm_example.m]] (an example of using [=IA2RMS=] to sample from N(0,1)).
to:
 * Useful code snippets: [[Attach:tauvsd.m | tauvsd.m]] (an example of running AM on multivariate normals), [[Attach:stdnorm_example.m | stdnorm_example.m]] (an example of using [=IA2RMS=] to sample from N(0,1)), [[Attach:mcgaus.m | mcgaus.m]] (RWM for N(0,1)).
August 01, 2016, at 09:34 AM by 139.80.236.40 -
Changed line 41 from:
 * Useful code snippets: [[Attach:tauvsd.m | tauvsd.m]] (an example of running AM on multivariate normals), [[Attach:stdnorm_example.m | stdnorm_example.m]] (an example of using IA2RMS to sample from N(0,1)).
to:
 * Useful code snippets: [[Attach:tauvsd.m | tauvsd.m]] (an example of running AM on multivariate normals), [[Attach:stdnorm_example.m | stdnorm_example.m]] (an example of using [=IA2RMS=] to sample from N(0,1)).
August 01, 2016, at 09:33 AM by 139.80.236.40 -
Added line 41:
 * Useful code snippets: [[Attach:tauvsd.m | tauvsd.m]] (an example of running AM on multivariate normals), [[Attach:stdnorm_example.m | stdnorm_example.m]] (an example of using IA2RMS to sample from N(0,1)).
July 28, 2016, at 12:36 PM by 139.80.236.40 -
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 * Inverse Problems [[https://coursesupport.physics.otago.ac.nz/wiki/pmwiki.php/ELEC445/HomePage?action=download&upname=IPNotes2016.pdf|2016 version of the course notes]]
to:
 * ELEC445 Inverse Problems [[https://coursesupport.physics.otago.ac.nz/wiki/pmwiki.php/ELEC445/HomePage?action=download&upname=IPNotes2016.pdf|course notes]]
July 27, 2016, at 09:36 AM by 139.80.236.40 -
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 *John Bardsley's [[http://www.math.umt.edu/bardsley/papers/MCMCforUQinInverseProblems.pdf | RTO paper]]
to:
 *Paper on MCMC using an approximation, ADAMH
July 27, 2016, at 09:34 AM by 139.80.236.40 -
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*''Lecture 4:'' Algorithmic Efficiency

*''Lecture 5:'' Inverse Diffusion Problem
*''Lecture 6:'' Image Reconstruction
*''Lecture 7:'' Linear/Gaussian problems
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*''Lecture 4:'' Inverse Diffusion Problem
*''Lecture 5:'' Image Models
*''Lecture 6:'' Linear-Gaussian Inverse Problems
 
*Paper on MTO for image deblurring
*''Lecture 7:'' Approximations
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 *[[Attach:Ass1_2014.pdf | Problem sheet]]
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 *[[Attach:Ass1_2016.pdf | Problem sheet]]
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 *[[Attach:Ass2_2014.pdf | Problem sheet]]
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 *[[Attach:Ass2_2016.pdf | Problem sheet]]
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 *[[Attach:Ass3_2014.pdf | Problem sheet]]
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 *[[Attach:Ass3_2016.pdf | Problem sheet]]
July 27, 2016, at 09:29 AM by 139.80.236.40 -
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 *AM: [[Attach:RobertsRosenthal2009 | Roberts and Rosenthal 2009 paper]] and [[http://helios.fmi.fi/~lainema/mcmc/ | Marko Laine's MCMC toolbox]]
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 *AM: [[Attach:RobertsRosenthal2009.pdf | Roberts and Rosenthal 2009 paper]] and [[http://helios.fmi.fi/~lainema/mcmc/ | Marko Laine's MCMC toolbox]]
July 27, 2016, at 09:28 AM by 139.80.236.40 -
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 *AM: Roberts and Rosenthal 2009 paper and Marko Laine's MCMC toolbox
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 *AM: [[Attach:RobertsRosenthal2009 | Roberts and Rosenthal 2009 paper]] and [[http://helios.fmi.fi/~lainema/mcmc/ | Marko Laine's MCMC toolbox]]
July 27, 2016, at 09:18 AM by 139.80.236.40 -
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*''Lecture 2: ''Evaluating Expectations: Monte Carlo and Markov chains in few dimensions
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*''Lecture 2: ''Evaluating Expectations, MH MCMC proposals in few dimensions
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 *[=IA2RMS=]: paper and Matlab package
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 *[=IA2RMS=]: [[Attach:MartinoReadLuengo2015.pdf | Martino Read Luengo 2015 paper]] and [[http://a2rms.sourceforge.net/ | Matlab package]]
July 27, 2016, at 09:05 AM by 139.80.236.40 -
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*''Lecture 3:'' Adaptive MCMCs and Efficiency
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*''Lecture 3:'' Adaptive [=MCMCs=] and Efficiency
July 27, 2016, at 09:04 AM by 139.80.236.40 -
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 *=IA2RMS=: paper and Matlab package
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 *[=IA2RMS=]: paper and Matlab package
July 27, 2016, at 09:03 AM by 139.80.236.40 -
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 *IA2RMS: paper and Matlab package
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 *=IA2RMS=: paper and Matlab package
July 27, 2016, at 09:02 AM by 139.80.236.40 -
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''Lectures and Tutorials:'' There is a 2-hour lecture and 1-hour tutorial per week
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*''Lecture 2: ''Expectations
 *Adaptive rejection paper by Gilks Tan Best
*''Lecture 3:'' MCMC basics
 
*
to:
*''Lecture 2: ''Evaluating Expectations: Monte Carlo and Markov chains in few dimensions
*''Lecture 3:'' Adaptive MCMCs and Efficiency
 
*IA2RMS: paper and Matlab package
 *AM: Roberts and Rosenthal 2009 paper and Marko Laine's MCMC toolbox
 *Ulli Wollf's [[http://www.physik.hu-berlin.de/com/ALPHAsoft/ | UWerr MatLab code]] and documentation
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 *Ulli Wollf's [[http://www.physik.hu-berlin.de/com/ALPHAsoft/ | UWerr MatLab code]] and documentation
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July 27, 2016, at 08:52 AM by 139.80.236.40 -
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 * Inverse Problems [[Attach:IPNotes2016.pdf|2016 version of the course notes]]
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 * Inverse Problems [[https://coursesupport.physics.otago.ac.nz/wiki/pmwiki.php/ELEC445/HomePage?action=download&upname=IPNotes2016.pdf|2016 version of the course notes]]
July 27, 2016, at 08:51 AM by 139.80.236.40 -
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 * Inverse Problems course notes [[http://www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/roberts/st911/notes2012partiii.pdf | notes on Statistical Inference]]
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 * Inverse Problems [[Attach:IPNotes2016.pdf|2016 version of the course notes]]
July 27, 2016, at 08:49 AM by 139.80.236.40 -
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!Module 412: Computational Inference
Module 412 develops '''Computational Inference''':
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!ELEC 446: Computational Inference
ELEC 446 develops '''Computational Inference''':
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''Assessment:'' 30% assignments, 70% Exam
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''Assessment:'' 30% assignments, 70% Project (ELEC446 will be internally assessed in 2016)
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 * Inverse Problems course notes [[http://www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/roberts/st911/notes2012partiii.pdf | notes on Statistical Inference]]
July 27, 2016, at 08:45 AM by 139.80.236.40 -
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[[Mod412_2015 | Module 412 in 2015]]
July 27, 2016, at 08:32 AM by 139.80.80.3 -
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(:notitle:)
!Module 412: Computational Inference
Module 412 develops '''Computational Inference''':
Bayesian inference for uncertainty quantification, stochastic modelling and MCMC sampling,
advanced Monte Carlo strategies, imaging and machine vision.

Semester: 2

''Recommended Preparation:'' Inverse Problems and Imaging module

''Lecturer:'' [[http://elec.otago.ac.nz/w/index.php/Colin_Fox | Colin Fox]]. Room 503. Ph 4797806. colin.fox 'at' otago.ac.nz

''Assessment:'' 30% assignments, 70% Exam

----

Resources:

*''Lecture 1: ''Problem and Goals
 *Gareth Roberts' [[http://www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/roberts/st911/notes2012partiii.pdf | notes on Statistical Inference]]
*''Lecture 2: ''Expectations
 *Adaptive rejection paper by Gilks Tan Best
*''Lecture 3:'' MCMC basics
 *
*''Lecture 4:'' Algorithmic Efficiency
 *Ulli Wollf's [[http://www.physik.hu-berlin.de/com/ALPHAsoft/ | UWerr MatLab code]] and documentation
*''Lecture 5:'' Inverse Diffusion Problem
*''Lecture 6:'' Image Reconstruction
*''Lecture 7:'' Linear/Gaussian problems
 *John Bardsley's [[http://www.math.umt.edu/bardsley/papers/MCMCforUQinInverseProblems.pdf | RTO paper]]
*''Lecture 8:'' Counting objects
 *

*''Assignment 1:''
 *[[Attach:Ass1_2014.pdf | Problem sheet]]
 *Matlab code for diffusion problem: [[Attach:Main.m | Main.m]] [[Attach:heat.m | heat.m]]
*''Assignment 2:''
 *[[Attach:Ass2_2014.pdf | Problem sheet]]
 *Matlab code for deblurring jupiter image:  [[Attach:jupiter1.tif | jupiter1.tif]]  [[Attach:jupiter.m | jupiter.m]]  [[Attach:deconv1.m | deconv1.m]]
*''Assignment 3:''
 *[[Attach:Ass3_2014.pdf | Problem sheet]]
 *Image of good and bad cells in Matlab mat format [[Attach:slide.mat | slide.mat]], or as [[Attach:slide.tif | slide.tif]]. Matlab code [[Attach:makefake.m | makefake.m]] that generated the image, and uses functions [[Attach:putgood.m | putgood.m]] and [[Attach:putbad.m | putbad.m]].



Links:

[[http://www.otago.ac.nz/physics/postgraduate/postgraduate-papers/otago050695.html#Mod12 | Department of Physics 400-level information]]