Fabian Scheipl

About Fabian Scheipl

Fabian Scheipl, With an exceptional h-index of 35 and a recent h-index of 30 (since 2020), a distinguished researcher at Ludwig-Maximilians-Universität München, specializes in the field of Statistics, Bayesian Statistics, Functional Data Analysis, Additive Models, Survival Analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

Developing open source educational resources for machine learning and data science

DCSI--An improved measure of cluster separability based on separation and connectedness

Enhancing cluster analysis via topological manifold learning

Reproduzierbare und replizierbare Forschung

Multivariate functional additive mixed models

Package ‘ordPens’

Protein intake and outcome of critically ill patients: analysis of a large international database using piece-wise exponential additive mixed models

Package ‘registr’

Fabian Scheipl Information

University

Position

/ Munich Center for Machine Learning

Citations(all)

7226

Citations(since 2020)

3871

Cited By

4718

hIndex(all)

35

hIndex(since 2020)

30

i10Index(all)

59

i10Index(since 2020)

51

Email

University Profile Page

Google Scholar

Fabian Scheipl Skills & Research Interests

Statistics

Bayesian Statistics

Functional Data Analysis

Additive Models

Survival Analysis

Top articles of Fabian Scheipl

Developing open source educational resources for machine learning and data science

2023/12/2

DCSI--An improved measure of cluster separability based on separation and connectedness

arXiv preprint arXiv:2310.12806

2023/10/19

Fabian Scheipl
Fabian Scheipl

H-Index: 30

Enhancing cluster analysis via topological manifold learning

Data Mining and Knowledge Discovery

2023/9/29

Reproduzierbare und replizierbare Forschung

2023/9/1

Multivariate functional additive mixed models

Statistical Modelling

2023/8

Fabian Scheipl
Fabian Scheipl

H-Index: 30

Sonja Greven
Sonja Greven

H-Index: 23

Package ‘ordPens’

2023/7/10

Fabian Scheipl
Fabian Scheipl

H-Index: 30

Protein intake and outcome of critically ill patients: analysis of a large international database using piece-wise exponential additive mixed models

Critical Care

2022/12

Package ‘registr’

2022/10/14

Package ‘spikeSlabGAM’

2022/10/14

Fabian Scheipl
Fabian Scheipl

H-Index: 30

A geometric framework for outlier detection in high-dimensional data

arXiv preprint arXiv:2207.00367

2022/7/1

Florian Pfisterer
Florian Pfisterer

H-Index: 0

Fabian Scheipl
Fabian Scheipl

H-Index: 30

Correction to “A Penalized Framework for Distributed Lag Non-Linear Models” by Antonio Gasparrini, Fabian Scheipl, Ben Armstrong, and Michael G. Kenward; 73, 938–948, September …

Biometrics

2022/6

Fabian Scheipl
Fabian Scheipl

H-Index: 30

Ben Armstrong
Ben Armstrong

H-Index: 1

Statistical inference for ordinal predictors in generalized additive models with application to bronchopulmonary dysplasia

BMC research notes

2022/3/22

Fabian Scheipl
Fabian Scheipl

H-Index: 30

A geometric perspective on functional outlier detection

Stats

2021/11/24

Fabian Scheipl
Fabian Scheipl

H-Index: 30

Registration for incomplete non-Gaussian functional data

arXiv preprint arXiv:2108.05634

2021/8/12

Unsupervised functional data analysis via nonlinear dimension reduction

arXiv preprint arXiv:2012.11987

2020/12/22

Fabian Scheipl
Fabian Scheipl

H-Index: 30

A General Machine Learning Framework for Survival Analysis

arXiv preprint arXiv:2006.15442

2020/6/27

Package ‘mvtnorm’

Journal of Computational and Graphical Statistics

2020/6/9

Comments on: Inference and computation with Generalized Additive Models and their extensions

TEST

2020/6

Sonja Greven
Sonja Greven

H-Index: 23

Fabian Scheipl
Fabian Scheipl

H-Index: 30

Reported and recorded sleepiness in obesity and depression

Frontiers in psychiatry

2020/4/2

See List of Professors in Fabian Scheipl University(Ludwig-Maximilians-Universität München)

Co-Authors

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