About me

I am a PhD student at the Seminar for Statistics (SfS) under the supervision of Peter Bühlmann. Additionally, I act as group coordinator for the SfS / group 2.

List of publications

Peer-reviewed

Schultheiss, C., and Bühlmann, P. (2024). Assessing the overall and partial causal well-specification of nonlinear additive noise models. Journal of Machine Learning Research 25, (159): 1-41
Schultheiss, C., Bühlmann, P. and Yuan, M. (2024). Assessing the goodness of fit of linear regression via higher-order least squares. Journal of the American Statistical Association 119, 1019-1031
Immer, A., Schultheiss, C., Vogt, J. E., Schölkopf, B., Bühlmann, P., and Marx, A. (2023). On the identifiability and estimation of causal location-scale noise models. Proceedings of the 40th International Conference on Machine Learning, PMLR 202:14316-14332
Schultheiss, C. and Bühlmann, P. (2023). On the pitfalls of Gaussian likelihood scoring for causal discovery. On the pitfalls of Gaussian likelihood scoring for causal discovery. Journal of Causal Inference 11
Schultheiss, C., and Bühlmann, P. (2023). Ancestor regression in linear structural equation models. Biometrika 110, 1117-1124
Schultheiss, C., Renaux, C. and Bühlmann, P. (2021). Multicarving for high-dimensional post-selection inference. Electronic Journal of Statistics 15, 1695-1742

Preprint

Schultheiss, C., and Bühlmann, P. (2024). Ancestor regression in structural vector autoregressive models. arXiv:2403.03778
Langer, N., Weber, M., Hebling Vieira, B., Strzelczyk, D., Wolf, L., Pedroni, A., Heitz, J., Müller, S., Schultheiss, C., Tröndle, M., Arango Lasprilla, J., Rivera, D., Scarpina, F., Zhao, Q., Leuthold, R., Wehrle, F., Jenni, O., Brugger, P., Zaehle, T., Lorenz, R. and Zhang, C. (2024). Automating clinical assessments of memory deficits: Deep Learning based scoring of the Rey-Osterrieth Complex Figure. bioRxiv

Teaching

TA

Linear Algebra I + II for 1st year Mechanical Engineering students; 2016 - 2018 (6 semesters)
Fluid Dynamics I for 2nd year Mechanical Engineering students; FS 2017
Computational Statistics; FS 2021, FS 2022, FS 2023 (coordinator and TA)

Replacement lecturer

Computational Statistics, for various levels and programs, FS 2022 (3 hours)
Mathematik IV: Statistik, for 2nd year Environmental Sciences, Food Science, Agricultural Sciences, and Earth and Climate Sciences students, HS 2022, HS 2023 (8 hours)

Review

I have reviewed for several journals and a conference