Workshop "BART - Bayesian additive regression trees"

Workshop of the IBS-DR working groups Ecology and Envoronment, Bayes Methods, Spatial Statistics as well as the DFFA working group Biometry.
Freising (or online), April 24-26, 2024.

 

Venue:
    Bayerische Landesanstalt für Wald und Forstwirtschaft (LWF)
    Hans-Carl-von-Carlowitz-Platz 1
    85354 Freising
    48° 24' 00.1"N 11° 43' 03.4"E

 

Announcement and call for papers

 

(Preliminary) program
(exact order of presentations still to be finalized):

 

Wednesday, April 24, 2024:

16:00-16:30	Welcome
16:30-18:00	Colin Carlson (Georgetown University, Washington D.C.): BART - Bayesian Additive Regression Trees
18:00-18:30	Tobias Mette (LWF Bayern): Purposive sampling across different data sources for a robust forest risk assessment by species distribution modelling	[abstract]
19:30	Joint dinner at Bräustüberl Weihenstephan

 

Thursday, April 25, 2024:

09:00-10:30	Jeremy Yoder (California State University, Northridge): Tutorial: Bayesian additive regression trees (Part I)
10:30-11:00	Break
11:00-11:30	Hendrik Edelhoff (LWF Bayern): Bayesian implementation of a spatial capture recapture model to infer sex-specific density gradients in a mountain ungulate	[abstract]
11:30-12:00	Leonie Gass (University of Bayreuth): Next forest generation - predicting current forest regeneration	[abstract]
12:00-12:30	Johannes Ponge (University of Münster): Agent-based simulations in spatial epidemiology	[abstract]
12:30-14:00	Lunch break
14:00-15:30	Jeremy Yoder (California State University, Northridge): Tutorial: Bayesian additive regression trees (Part II)
15:30-16:00	Break
16:00-17:30	Jeremy Yoder (California State University, Northridge): Tutorial: Bayesian additive regression trees (Part III)
17:30-17:45	Break
17:45-18:30	Working group meetings
19:00	Joint dinner at Schubauers am Dom

 

Friday, April 26, 2024:

09:00-10:30	Jeremy Yoder (California State University, Northridge): Tutorial: Bayesian additive regression trees (Part IV)
10:30-11:00	Break
11:00-11:30	Andreas Bender (LMU München): Evaluation of (machine learning) prediction models for spatially correlated data	[abstract]
11:30-12:00	Maximilian Pichler (University of Regensburg): Inductive bias in machine learning models - consequences for causal effects and predictions under feature collinearity	[abstract]
12:00-12:30	Closing

 

(note: all times are CEST (UTC+2))