Maximilian Pichler
Maximilian Pichler
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Machine learning algorithms to infer trait matching and predict species interactions in ecological networks
M Pichler, V Boreux, AM Klein, M Schleuning, F Hartig
Methods in Ecology and Evolution, 2019
Machine learning and deep learning—A review for ecologists
M Pichler, F Hartig
Methods in Ecology and Evolution 14 (4), 994-1016, 2023
A new joint species distribution model for faster and more accurate inference of species associations from big community data
M Pichler, F Hartig
Methods in Ecology and Evolution, 2021
Fixed or random? On the reliability of mixed‐effects models for a small number of levels in grouping variables
J Oberpriller, M de Souza Leite, M Pichler
Ecology and Evolution 12 (7), e9062, 2022
Linking functional traits and demography to model species-rich communities
L Chalmandrier, F Hartig, DC Laughlin, H Lischke, M Pichler, DB Stouffer, ...
Nature communications 12 (1), 2724, 2021
Novel community data in ecology-properties and prospects
F Hartig, N Abrego, A Bush, JM Chase, G Guillera-Arroita, MA Leibold, ...
Trends in Ecology & Evolution, 2024
Machine‐learning algorithms predict soil seed bank persistence from easily available traits
S Rosbakh, M Pichler, P Poschlod
Applied Vegetation Science 25 (2), e12660, 2022
Can predictive models be used for causal inference?
M Pichler, F Hartig
arXiv preprint arXiv:2306.10551, 2023
Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity
Y Li, C Devenish, MI Tosa, M Luo, DM Bell, DB Lesmeister, P Greenfield, ...
Philosophical Transactions of the Royal Society B 379 (1904), 20230123, 2024
‘cito': an R package for training neural networks using ‘torch'
C Amesöder, F Hartig, M Pichler
Ecography, e07143, 2024
Assembly processes inferred from eDNA surveys of a pond metacommunity are consistent with known species ecologies
W Cai, M Pichler, J Biggs, P Nicolet, N Ewald, RA Griffiths, A Bush, ...
bioRxiv, 2023.12. 12.571176, 2023
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