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Christoph Schultheiss
Christoph Schultheiss
PhD student, Seminar for Statistics, ETH Zürich
Verified email at stat.math.ethz.ch
Title
Cited by
Cited by
Year
On the identifiability and estimation of causal location-scale noise models
A Immer, C Schultheiss, JE Vogt, B Schölkopf, P Bühlmann, A Marx
International Conference on Machine Learning, 14316-14332, 2023
342023
Multicarving for high-dimensional post-selection inference
C Schultheiss, C Renaux, P Bühlmann
Electronic Journal of Statistics 15 (1), 1695-1742, 2021
172021
Ancestor regression in linear structural equation models
C Schultheiss, P Bühlmann
Biometrika 110 (4), 1117-1124, 2023
72023
Higher-order least squares: assessing partial goodness of fit of linear causal models
C Schultheiss, P Bühlmann, M Yuan
Journal of the American Statistical Association, 2023
52023
On the pitfalls of Gaussian likelihood scoring for causal discovery
C Schultheiss, P Bühlmann
Journal of Causal Inference 11 (1), 20220068, 2023
42023
The AI Neuropsychologist: Automatic scoring of memory deficits with deep learning
N Langer, M Weber, B Hebling Vieira, D Strzelczyk, L Wolf, A Pedroni, ...
bioRxiv, 2022
22022
Ancestor regression in structural vector autoregressive models
C Schultheiss, P Bühlmann
arXiv preprint arXiv:2403.03778, 2024
2024
Assessing the overall and partial causal well-specification of nonlinear additive noise models
C Schultheiss, P Bühlmann
Journal of Machine Learning Research 25 (159), 1-41, 2024
2024
Automating clinical assessments of memory deficits: Deep Learning based scoring of the Rey-Osterrieth Complex Figure
N Langer, M Weber, B Hebling Vieira, D Strzelczyk, L Wolf, A Pedroni, ...
bioRxiv, 2022.06. 15.496291, 2022
2022
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