PostDoc
Group for Theoretical Ecology
Faculty of Biology and Pre-Clinical Medicine
University of Regensburg
Universit?tsstra?e 31
93053 Regensburg
email: maximilian.pichler(at)biologie.uni-regensburg.de (?ffnet Ihr E-Mail-Programm)
room: E4._2.103
Research Interests
- Machine Learning and Deep Learning in Ecology
- Inference with Machine Learning and Deep learning
- Joint Species Distribution Models (jSDM)
- Trait-Matching in ecological networks
- Automatic Species Recognition
See also
Software:
Curriculum Vitae
| 2024- | PostDoc at University of Regensburg, Germany |
| 2018-2024 | PhD studies at University of Regensburg, Germany |
| 2016-2018 | Master studies in Biology at University of Regensburg, Germany |
| 2012-2016 | Bachelor studies in Biology at University of Regensburg, Germany |
Publications
- Pichler, M., & Hartig, F. (2023). Can predictive models be used for causal inference?. arXiv preprint arXiv:2306.10551. [preprint]
- Pichler, M., & Hartig, F. (2023). Machine learning and deep learning—A review for ecologists. Methods in Ecology and Evolution, 14(4), 994-1016. [journal]
- Pichler, M., & Hartig, F. (2021). A new joint species distribution model for faster and more accurate inference of species associations from big community data. Methods in Ecology and Evolution.[journal]
- Oberpriller, J., de Souza Leite, M., & Pichler, M. (2021). Fixed or random? On the reliability of mixed-effect models for a small number of levels in grouping variables. bioRxiv.[journal]
- Pichler, M., Boreux, V., Klein, A. M., Schleuning, M., & Hartig, F. (2020). Machine learning algorithms to infer trait‐matching and predict species interactions in ecological networks. Methods in Ecology and Evolution, 11(2), 281-293. [journal]