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Maximilian Pichler

     

PhD student
Group for Theoretical Ecology
Faculty of Biology and Pre-Clinical Medicine
University of Regensburg
Universitätsstraße 31
93053 Regensburg


email: maximilian.pichler@biologie.uni-regensburg.de
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
  • Automatic Species Recognition

See also

Software:

Curriculum Vitae

2018-now 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]

  1. Fakultät für Biologie und Vorklinische Medizin
  2. Ökologie und Naturschutzbiologie

Theoretische Ökologie

Leitung
Prof. Dr. Florian Hartig
Raum BIO E4_2.105
Tel +49-941 943-4316


Location
Universitätsstr. 31
93053 Regensburg

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