BAYES@AUSTRIA 2020

Program

Saturday, November 28

900
Welcome

Session I | Chair: Sylvia Frühwirth-Schnatter (WU Vienna)
905-950 Florian Huber (University of Salzburg)
Forecasting with Bayesian Non-Parametric Vector Autoregressive Models
950-1000 Short break
1000-1025 Florian Frommlet (Medical University of Vienna)
A Genetically Modified Mode Jumping MCMC Algorithm for Model Selection in Non-Standard Applications.
1025-1050 Jan Greve (WU Vienna)
Spying on the prior of the number of clusters and partition distributions in Bayesian cluster analysis
1050-1115 Markus Hainy (JKU Linz)
Bayesian Experimental Design for Models with Intractable Likelihoods via Supervised-Learning Methods
1115-1130 Short break

Session II | Florian Huber (University of Salzburg)
1130-1155 Niko Hauzenberger (University of Salzburg)
Dynamic Shrinkage Priors for Large Time-Varying Parameter Regressions Using Scalable Markov Chain Monte Carlo Methods
1155-1220 Paul Hofmarcher (University of Salzburg)
Bayesian Model Averaging: Review und Perspectives
1220-1245 Darjus Hosszejni (WU Vienna)
The Role of the stochvol Package in Bayesian Dynamic Covariance Estimation
1245-1345 Lunch

Session III | Chair: Bettina Grün (WU Vienna)
1345-1430 Helga Wagner (JKU Linz)
Bayesian modelling of treatment effects
1430-1440 Short break
1440-1505 Gregor Kastner (University of Klagenfurt)
Time-varying Risk Premia and Volatility Dynamics in Multi-Asset Class Returns.
1505-1530 Peter Knaus (WU Vienna)
The triple gamma – A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models
1530-1555 Gertraud Malsiner-Walli (WU Vienna)
Generalized mixtures of finite mixtures
1555-1610 Short break

Session IV | Chair: Helga Wagner (JKU Linz)
1610-1635 Nikolaus Umlauf (University of Innsbruck)
Scalable Distributional Regression
1635-1700 Laura Vana (WU Vienna)
Verification of spatio-temporal properties in a Bayesian model using signal spatio-temporal logic
1700-1725 Gregor Zens (WU Vienna)
Ultimate Pólya Gamma Samplers – Efficient MCMC for Possibly Imbalanced Binary and Categorical Data

1725 Closing