Fabian Scheipl

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 13

Top Venues

CoRR

Comput. Stat. Data Anal.

Teaching ML

WIREs Data. Mining. Knowl. Discov.

Ludwig Maximilians University Munich (PHD)

Education History

Ludwig Maximilians University Munich

PHD

Publications

Moritz Herrmann, Daniyal Kazempour, Fabian Scheipl, Peer Kröger
Enhancing cluster analysis via topological manifold learning. Data Min. Knowl. Discov. 38 (3) (2024)
Jana Gauss, Fabian Scheipl, Moritz Herrmann
DCSI - An improved measure of cluster separability based on separation and connectedness. CoRR (2023)
Moritz Herrmann, Florian Pfisterer, Fabian Scheipl
A geometric framework for outlier detection in high-dimensional data. WIREs Data. Mining. Knowl. Discov. 13 (3) (2023)
Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science. Teaching ML (2022)
Moritz Herrmann, Florian Pfisterer, Fabian Scheipl
A geometric framework for outlier detection in high-dimensional data. CoRR (2022)
Moritz Herrmann, Daniyal Kazempour, Fabian Scheipl, Peer Kröger
Enhancing cluster analysis via topological manifold learning. CoRR (2022)
Moritz Herrmann, Fabian Scheipl
A geometric perspective on functional outlier detection. CoRR (2021)
Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science. CoRR (2021)
Andreas Bender, David Rügamer, Fabian Scheipl, Bernd Bischl
A General Machine Learning Framework for Survival Analysis. CoRR (2020)
Moritz Herrmann, Fabian Scheipl
Unsupervised Functional Data Analysis via Nonlinear Dimension Reduction. CoRR (2020)
Andreas Bender, David Rügamer, Fabian Scheipl, Bernd Bischl
A General Machine Learning Framework for Survival Analysis. ECML/PKDD (3) (2020)
Florian Pfisterer, Laura Beggel, Xudong Sun, Fabian Scheipl, Bernd Bischl
Benchmarking time series classification - Functional data vs machine learning approaches. CoRR (2019)
Jona Cederbaum, Fabian Scheipl, Sonja Greven
Fast symmetric additive covariance smoothing. Comput. Stat. Data Anal. 120 (2018)
Andrada E. Ivanescu, Ana-Maria Staicu, Fabian Scheipl, Sonja Greven
Penalized function-on-function regression. Comput. Stat. 30 (2) (2015)
Karen Fuchs, Fabian Scheipl, Sonja Greven
Penalized scalar-on-functions regression with interaction term. Comput. Stat. Data Anal. 81 (2015)
Jeff Goldsmith, Fabian Scheipl
Estimator selection and combination in scalar-on-function regression. Comput. Stat. Data Anal. 70 (2014)
Simon N. Wood, Fabian Scheipl, Julian J. Faraway
Straightforward intermediate rank tensor product smoothing in mixed models. Stat. Comput. 23 (3) (2013)
Fabian Scheipl, Thomas Kneib
Locally adaptive Bayesian P-splines with a Normal-Exponential-Gamma prior. Comput. Stat. Data Anal. 53 (10) (2009)
Fabian Scheipl, Sonja Greven, Helmut Küchenhoff
Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models. Comput. Stat. Data Anal. 52 (7) (2008)

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Publication Activity (10 Years)

Top Topics

Top Venues

Fabian Scheipl