July to December 1998
Organisers: W J Fitzgerald (Cambridge), R L Smith (University of North Carolina), A Walden (Imperial College, London) and P C Young (Lancaster University)
Organisers: WJ Fitzgerald (Cambridge), RL Smith (North Carolina),
AT Walden (Imperial), PC Young (Lancaster)
The main focus and thrust of this workshop will be that Bayesian methods provide a unifying methodology whereby different kinds of mathematical models may be examined within a common statistical framework. The workshop will bring together the statistical and computational expertise of leading statisticians and the modelling expertise of mathematicians and subject matter specialists, with the broad objective of developing new signal processing tools which make efficient use of modern computational resourc es while combining the most up-to-date research of both groups of specialists.
The workshop will take place at the start of a six month programme on Nonlinear and Nonstationary Signal Processing to be held at the Isaac Newton Institute in Cambridge (July - Dec 1998), where it is hoped that many of the problems identified during the workshop will be studied in detail by the participants.
7pm - ...(please note change from 6pm) Reception at Christ's College
09.00 - 10.00 Registration
10.00-11.00 W J Fitzgerald (Cambridge)
An Introduction to Bayesian Signal Processing I
11.00-11.30 Coffee
11.30-12.30 W J Fitzgerald (Cambridge)
An Introduction to Bayesian Signal Processing II
12.30-14.00 Lunch
14.00-15.00 C Robert (Paris)
Latent Variable Models
15.00-15.30 Tea
15.30-16.30 C Robert (Paris)
The Simulated Likelihood Method
10.00-11.00 P J W Rayner (Cambridge)
Non-linear Signal Modelling - a Tutorial I
11.00-11.30 Coffee
11.30-12.30 P J W Rayner (Cambridge)
Non-linear Signal Modelling - a Tutorial II
12.30-14.00 Lunch
14.00-15.00 J A Stark (NISS and Cambridge)
MCMC Methods for Multiple Changepoint Inference
15.00-15.30 F Gustafsson (Sweden)
Automotive applications on adaptive filtering and change
15.30-16.00 Tea
16.00-17.00 J Scargle (NASA)
Multiple Change Point Determination for Point Processes
10.00-11.00 C Bishop (Microsoft Research)
Introduction to Probabilistic Graphical Models I
11.00-11.30 Coffee
11.30-12.30 C Bishop (Microsoft Research)
Introduction to Probabilistic Graphical Models II
12.30-14.00 Lunch
14.00-15.00 D Spiegelhalter (Cambridge)
Bayesian graphical modelling of complex applications
15.00-15.30 Tea
15.30-16.30 Introduction to 'BUGS'
16.45 -17.45 David Mackay (Cambridge)
Latent Variable Models and Neural Networks
6.00- ... Wine reception and Buffet (Sponsored by Cambridge
Neurodynamics and Autonomy)
Posters
9.00-10.00 M Niranjan (Cambridge)
Bayesian Techniques in Speech Signal Processing
10.00-11.00 David Mackay (Cambridge)
State of the art in error correcting codes
11.00-11.30 Coffee
11.30-12.30 S J Godsill (Cambridge)
Bayesian methods for non-Gaussian signal processing
12.30-14.00 Lunch
14.00-14.30 F Gustafsson (Sweden)
MDL as a performance measure for choosing adaptive filters.
14.30-16.00 M Pitt (Imperial College)
Filtering and Smoothing for Non-Gaussian state space models
16.00-16.30 Tea
16.30-17.30 John Skilling (Cambridge)
Annealing and Ensembles
10.00-11.00 Giulio D'agostini (Rome)
A Tutorial on Measurement Uncertainty I
11.00-11.30 Coffee
11.30-12.30 Giulio D'agostini (Rome)
A Tutorial on Measurement Uncertainty II
12.30-14.00 Lunch
14.00-15.00 Siddhartha Chib, Neil Shephard and Ola Elerian
Likelihood inference for discretely observed non-linear diffusions
15.00-16.00 V Krishnamurthy
Iterative Maximum A-posteriori Sequence Estimation for Nonlinear Systems
16.00-16.30 Tea
16.30-17.30 A Hyvarinen (Finland)
Independent Component Analysis, Blind Source Separation, and Projection
Pursuit
19.30 Conference Dinner (Christ's College)
9.00-10.00 Mike West (Duke)
Decomposition Methods In Nonstationary Signal Processing
10.00-11.00 A Walden (Imperial College)
Scale Analysis of Time Series
11.00-11.30 Coffee
11.30-12.30 R Baraniuk
Wavelet-domain statistical signal and image processing using hidden
markov models
12.30-14.00 Lunch
Cricket Match and Barbeque
10.00-11.00 R Nowak
Bayesian Analysis of Poisson Processes: A Wavelet-Based Approach
11.00-11.30 Coffee
11.30-12.30 B Vidakovic (Duke)
Nonlinear Bayesian Shrinkage in the Wavelet Domain by Mixtures of Normal-Inverse
Gamma Priors
12.30-14.00 Lunch
14.00-15.00 P Mueller (Duke)
Bayesian Inference with Wavelets: The Non-Equidistant Case - An MCMC
Scheme
15.00-16.00 D Denison (Imperial College)
Nonparametric Bayesian models for regression
16.00-16.30 Tea
16.30-17.00 M Hild (Cambridge)
A Non-Probabilistic Measure of Plausibility
16.00 - 18.30 Posters
10.00 -11.00 N Shephard (Oxford)
An example of signal processing in finance: stochastic volatility
11.00-11.30 Coffee
11.30-12.30 P C Young (Lancaster)
Recursive estimation of time and state dependent parameters using fixed
interval smoothing
12.30-14.00 Lunch
14.00-14.30 A Doucet (Cambridge)
MCMC Methods for Blind Bayesian Deconvolution
14.30-15.00 C Andrieu (Cambridge)
MCMC Methods for Bayesian Spectral Analysis
15.00-16.00 AP Quinn (TCD)
Bayesian perspectives on signal identification
16.00-16.30 Tea
16.30-17.30 E Moulines and O Cappe (Paris)
Estimation via simulation with applications to statistical inference
in incomplete data models
9.00 -11.00 R Smith
Spatial Statistics
11.00-11.30 Coffee
11.30-12.30 S Wilson (TCD, Dublin)
Bayesian Image Segmentation
12.30-14.00 Lunch
14.00-15.00 A Kokaram (TCD, Dublin)
Joint Detection and Removal of Missing Data for Degraded Image Sequences
15.00-16.00 A Hero
Robust Entropy Estimation via Pruned Minimal Spanning Trees
16.00-16.30 Tea
16.30-17.30 Roderick Murray-Smith (Denmark)
Multiple Model Approaches to Empirical Modelling
10.00 -11.00 P Djuric (Stony Brook)
On variable duration Hidden Markov Models
11.00-11.30 Coffee
11.30-12.30 R Elliott (Canada)
Kronecker's Lemma and parameter estimation
12.30-14.00 Lunch
14.00-15.00 J Scargle (NASA)
Exciting Events in the Universe
15.00-16.00 R Kohn (New South Wales)
Inference for dynamic mixture models
16.00-16.30 Tea
16.30-17.30 Leonard Smith (Oxford)
Shadowing and the dynamics of uncertainty within a given model class
17.30-18.00 Closing words
1) Albert C.S. Wong
On a Mixture Autoregressive Model
2) Maria Eduarda R. P. A. da Silva
Frequency Domain Estimation of Hidden Markov Autoregressive Models.
3) Dr. Gul Ergun
Bayesian Modelling of the Istanbul Stock Exchange.
4) Bart Mertens
Bayesian prediction with latent growth models for on-line monitoring
in cheese manufacture.
6) James Heald
Use of the Evidence method to estimate appropriate measurement and dynamical
noise levels for chaotic noise reduction
7) V. B. Mani Mohan and W. J. Fitzgerald
Bayesian estimation in the cyclic correlation domain
8) Jacek Noga and W. J. Fitzgerald
Hybrid Monte Carlo for State Space Models
9) Simon Barker
MCMC approaches applied to Image Segmentation.
10) Jasvinder Kandola
Statistical Modelling of Manufacturing Processes.
11) Colin Campbell and S J Godsill
Simulation for conditionally Gaussian time series using a stochastic
version of EM
12) J A Stark, W J Fitzgerald and S B Hladky
MCMC Modelling of Ion Channels
13) B Kannan and W J Fitzgerald
A Numerical Bayesian Approach for DOA and Frequency Estimation of Exponential
Signals in Gaussian and Non-Gaussian Noise.
14) JFG de Freitas
Sequential Monte Carlo Methods Applied to Neural Networks in Non-Linear,
Non-Stationary Environments
15) Mike Davies
Blind Signal Separation using Independent AR models
16) T Clapp
Fixed-lag Smoothing using Sequential Importance Sampling
17) Jaco Vermaak
MCMC Estimation of a Speech Production Model for Voiced Sounds
18) David Leporini
Reversible jump MCMC methods for wavelet packet decompostion of transient
signals
19) Paul T. Troughton and Simon J. Godsill
MCMC Methods for Restoration of Nonlinearly Distorted
Autoregressive Signals
20) Bruno Sanso ISDS, Duke University
A Multisite Dynamic Model for Rainfall
21)Paul Walmsley, Simon Godsill and Peter Rayner
Multidimensional Optimisation of Harmonic Signals