Program

blobid32.png

 

Sunday:


17:00 – 17:45: Introduction & Welcome (André R. Brodtkorb and Arnoldo Frigessi) [pdf1] [pdf2]
17:45 – 18:30: Bayesian Inference: What and Why? (Elja Arjas) [pdf]
19:30:     Dinner

Monday:


09:00 – 10:30: Introduction to Point Processes (Aila Särkkä) [pdf]
Inhomogeneity, Anisotropy, and Replications (Aila Särkkä) [pdf]
10:30 – 15:00: Break
15:00 – 16:30: Object Oriented Data Analysis: Introduction and FDA (Steve Marron)
Object Oriented Data Analysis: Manifold data & Backwards PCA (Steve Marron) [pdf]
16:30 – 17:00: Coffee
17:00 – 18:30: Bayesian Inference with Approximate Bayesian Computation and Pseudolikelihood (Jukka Corander) [pdf1] [pdf2] [paper1] [paper2] [paper3] [paper4] [paper5]
19:30: Dinner

Tuesday:


09:00 – 10:30: Diffeomorphometry and Shape Spaces Under Diffeomorphic Action (Laurent Younes) [pdf]
10:30 – 15:00: Break
15:00 – 16:30:

Introduction to Network Modelling in Genomics (Ernst Wit) [pdf]
Networks and Sparse Graphical Models (Ernst Wit) [pdf]

16:30 – 17:00: Coffee
17:00 – 18:30: High-Dimensional and Complex Data: The Example of Data on Functional Spaces (Laura Sangalli) 
Statistical and Numerical Techniques for Spatial  Functional Data Analysis (Laura Sangalli) [pdf]
19:30: Dinner

Wednesday:


09:00 – 10:30:

Causal Inference from Longitudinal Data: A Bayesian Approach (Elja Arjas) [pdf]
10:30 – 15:00: Break
15:00 – 15:45: Causal Inference from Longitudinal Data: A Bayesian Approach (Elja Arjas) [pdf]
15:45 – 16:30: Example: Epidermal Nerve Fiber Patterns (Replications, Non-Spatial Covariates)  (Aila Särkkä) [pdf]
16:30 – 17:00: Coffee
17:00 – 17:45: Example: Polar Ice (Anisotropy and Inhomogeneity) (Aila Särkkä) [pdf]
17:45 – 18:30: Poster session
19:30: Dinner

Thursday:


09:00 – 10:30: Diffeomorphometry and Statistics with Examples (Laurent Younes) [pdf]
10:30 – 15:00: Break
15:00 – 16:30: Population Monte Carlo and Population Markov Chain Monte Carlo Methods with  applications (Jukka Corander) [pdf]
16:30 – 17:00: Coffee
17:00 – 18:30:

Model selection in penalized Gaussian graphical models (Ernst Wit) [pdf]
Inference of non-linear genomic dynamics (Ernst Wit) [pdf]
A fib, a lie, and statistics (Ernst Wit) [pdf]

19:30: Dinner

Friday:


09:00 – 10:30: Object Oriented Data Analysis: Classification & Visualization (Steve Marron)
Object Oriented Data Analysis: High Dimension Low Sample Size Mathematical Statistics (Steve Marron) [pdf]
10:30 – 11:00: Break (Check out)
11:00 – 12:30: Spatial Regression with Partial Differential Equation Regularizations (Laura Sangalli)
Data Spatially Distributed on Manifolds (Laura Sangalli) [pdf]
12:30 – 14:00: Lunch
14:00 – 16:00: Departure by train to Oslo / Bergen
 

Published January 16, 2014