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  • Das nächste planmäßige e-Rundschreiben erscheint im Mai 2024

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:

16:00-16:30Welcome
16:30-18:00Jeremy Yoder (California State University, Northridge): Tutorial: Bayesian additive regression trees (Part I)
18:00-18:30Tobias Mette (LWF Bayern): Purposive sampling across different data sources for a robust forest risk assessment by species distribution modelling[abstract]
19:30Joint dinner at Bräustüberl Weihenstephan

 

Thursday, April 25, 2024:

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

 

Friday, April 26, 2024:

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

 

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