3 citations · 7 across the 3 of their papers we have counts for
8 papers
A geometric perspective on functional outlier detection
Moritz Herrmann, Fabian Scheipl
We consider functional outlier detection from a geometric perspective, specifically: for functional data sets drawn from a functional manifold which is defined by the data's modes…
Registration for Incomplete Non-Gaussian Functional Data
Alexander Bauer, Fabian Scheipl, Helmut Küchenhoff +1
Accounting for phase variability is a critical challenge in functional data analysis. To separate it from amplitude variation, functional data are registered, i.e., their observed…
Multivariate Functional Additive Mixed Models
Alexander Volkmann, Almond Stöcker, Fabian Scheipl +1
Multivariate functional data can be intrinsically multivariate like movement trajectories in 2D or complementary like precipitation, temperature, and wind speeds over time at a giv…
Unsupervised Functional Data Analysis via Nonlinear Dimension Reduction
Moritz Herrmann, Fabian Scheipl
In recent years, manifold methods have moved into focus as tools for dimension reduction. Assuming that the high-dimensional data actually lie on or close to a low-dimensional nonl…
A General Machine Learning Framework for Survival Analysis
Andreas Bender, David Rügamer, Fabian Scheipl +1
The modeling of time-to-event data, also known as survival analysis, requires specialized methods that can deal with censoring and truncation, time-varying features and effects, an…
Benchmarking time series classification -- Functional data vs machine learning approaches
Florian Pfisterer, Laura Beggel, Xudong Sun +2
Time series classification problems have drawn increasing attention in the machine learning and statistical community. Closely related is the field of functional data analysis (FDA…