CRiSM Workshop "Bayesian Inference for High-Dimensional data": Programme

 

  Monday, April 14th    Tuesday, April 15th    Wednesday, April 16th 
           
9:30-10:30 

Keynote presentation:

 Doug Nychka 

  9:30-10:30

Keynote presentation:

 Carl Rasmussen 

 9:30-10:30

Keynote presentation:

 Nils Hjort 
10:30-11:10

Themed session:

 John Haslett 

  10:30-11:10

Themed session:

 Yee Whye Teh 

  10:30-11:10

Themed session:

 Feng Liang 
11:10-11:40 Break 11:10-11:40 Break  11:10-11:40 Break
11:40-12:20

Themed session:

 Bruno Sanso' 

  11:40-12:20

Themed session:

 Jurgen van Gael 

  11:40-12:20

Themed session:

 Longhai Li 
12:20-13:00

Themed session:

 Jonathan Rougier 

  12:20-13:00

Themed session:

 Mahmoud Zarepour

 12:20-13:00

Themed session:

 Adrian Dobra 
13:00-14:00 Lunch break 13:00-14:00 Lunch break 13:00-14:00 Lunch break
14:00-15:00

Keynote presentation:

 Rob Kass 

  14:00-14:30

Contributed session:

 Yves F. Atchade 

  14:00-15:00

Keynote presentation:

 David Madigan 
15:00-15:40

Themed session:

 Jeffrey Morris 

  14:30-15:00

Contributed session:

 Li Chen

 15:00-15:40

Themed session:

 Malay Ghosh 
15:40-16:10 Break     15:40-16:10 Break
16:10-16:50

Themed session:

 Darren Wilkinson 

  15.00-15.30

Contributed session:

Alexandra Schmidt 

 16:10-16:50

Themed session:

 Michele Guindani 
16:50-17:30

Themed session:

 Vilda Purutcuoglu

 15:30-16:00 Break
  16:50-17:30

Themed session:

 Volker Schmid 
17:30-19:00 Workshop Mixer  16:00-19:00 Poster Session
 17:30-19:00  
19:00 Dinner 19:00 Dinner 19:00 Dinner

 

Topics of keynote presentations:


Nils Hjort: Finding influential regressors in p > > n models.

Robert E. Kass: Challenges in Analyzing Neural Spike Train Data.

Doug Nychka: Reconstructing past climate using hierarchical models.

Carl Rasmussen: Data Analysis using Gaussian Processes.

David Madigan: High-dimensional Bayesian Classifiers.

Topics of invited presentations:

 

Malay Ghosh: Gene Expression-Based Glioma Classification Using Hierarchical Bayesian Vector Machines.

Michele Guindani: The Optimal Discovery Procedure and Bayesian Decision Rules.

John Haslett: Modelling the Paleoclimate.

Feng Liang: Bayesian Learning with Overcomplete Sets.

Jeffrey Morris: Bayesian Inference for High Dimensional Functional and Image Data using Functional Mixed Models.

Bruno Sanso': A Climatology for North Atlantic Sea Surface Temperatures.

Yee Whye Teh: Bayesian Language Models.

Darren Wilkinson: High-throughput data for systems biology modelling.