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Veröffentlichungsdatum
Anzahl der Publikationen: 3
2023
Rügamer, David 
ORCID: https://orcid.org/0000-0002-8772-9202; Baumann, Philipp F. M.; Kneib, Thomas und Hothorn, Torsten
(2023):
Probabilistic time series forecasts with autoregressive transformation models.
In: Statistics and Computing, Bd. 33, Nr. 2
[PDF, 653kB]
ORCID: https://orcid.org/0000-0002-8772-9202; Baumann, Philipp F. M.; Kneib, Thomas und Hothorn, Torsten
(2023):
Probabilistic time series forecasts with autoregressive transformation models.
In: Statistics and Computing, Bd. 33, Nr. 2
[PDF, 653kB]
2021
Baumann, Philipp F. M. ORCID: https://orcid.org/0000-0001-8066-1615; Hothorn, Torsten ORCID: https://orcid.org/0000-0001-8301-0471 und Rügamer, David ORCID: https://orcid.org/0000-0002-8772-9202
(2021):
Deep Conditional Transformation Models.
In: Oliver, Nuria; Pérez-Cruz, Fernando; Kramer, Stefan; Read, Jesse und Lozano, José A. (Hrsg.):
Machine Learning and Knowledge Discovery in Databases. Research Track. European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part III. Lecture Notes in Computer Science (LNAI), Bd. 12977. Cham: Springer. S. 3-18
ORCID: https://orcid.org/0000-0001-8066-1615; Hothorn, Torsten ORCID: https://orcid.org/0000-0001-8301-0471 und Rügamer, David ORCID: https://orcid.org/0000-0002-8772-9202
(2021):
Deep Conditional Transformation Models.
In: Oliver, Nuria; Pérez-Cruz, Fernando; Kramer, Stefan; Read, Jesse und Lozano, José A. (Hrsg.):
Machine Learning and Knowledge Discovery in Databases. Research Track. European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part III. Lecture Notes in Computer Science (LNAI), Bd. 12977. Cham: Springer. S. 3-18
Rugamer, David; Baumann, Philipp F. M. und Greven, Sonja
(2021):
Selective inference for additive and linear mixed models.
In: Computational Statistics & Data Analysis, Bd. 167, 107350