Contact
Cluster of Excellence “Machine Learning”
Maria-von-Linden-Str. 6
72076 Tübingen
+49 7071 2970895
jakob.schloer@uni-tuebingen.de
I’m a theoretical physicist mainly interested in climate data analysis using probabilistic models.
Research Interests
- Climate data analysis (i.e. spatial-temporal data from satellites and meteorology)
- El Nino Southern Oscillation diversity
- Generative models (Hidden Markov models, Variational Autoencoders)
- Representational learning
- Physics-informed Machine Learning (parameter inference, EnKF)
- Uncertainty quantification
- Climate networks
CV
I obtained my Bachelor in Physics at the University of Konstanz which was followed by a Masters in Physics at the University of Regensburg. During my studies I spent five months at the Weizmann Institute of Science in Israel and half a year at Bosch Research in Renningen. Since September 2020, I’m a PhD student in the Machine Learning for Climate Science group at the University of Tübingen and I’m part of the International Max-Planck Research School for Intelligent Systems. Privately, I love sports, nature and wildlife.
My CV can be found here.
Publications and conferences
2022
- Felix M. Strnad, Jakob Schlör, Christian Fröhlich, and Bedartha Goswami, Teleconnection patterns of different El Nino types revealed by climate network curvature, arXiv Preprint (2022), 2203.07035
2021
- Schlör, J. and Goswami, B.: A data-driven generative model for sea surface temperature fields in the tropical Pacific, EGU21-12362, EGU General Assembly 2021
2020
- Daniel Hernangómez-Pérez, Jakob Schlör, David A. Egger, Laerte L. Patera, Jascha Repp, and Ferdinand Evers,
Reorganization energy and polaronic effects of pentacene on NaCl films,
Phys. Rev. B 102, 115419 (2020)
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