Friedrich Leisch

About Friedrich Leisch

Friedrich Leisch, With an exceptional h-index of 65 and a recent h-index of 44 (since 2020), a distinguished researcher at Universität für Bodenkultur Wien, specializes in the field of R, statistical computing, biostatistics, cluster analysis, reproducible research.

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

Package ‘tth’

Explainable deep learning enhances robust and reliable real‐time monitoring of a chromatographic protein A capture step

Against the “one method fits all data sets” philosophy for comparison studies in methodological research

Validation of the Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT) questionnaire for adults

Applications of monitoring and tracing the evolution of clustering solutions in dynamic datasets

Internet

Monitoring Changes in Clustering Solutions: A Review of Models and Applications

A white paper on good research practices in benchmarking: The case of cluster analysis

Friedrich Leisch Information

University

Position

Institute of Statistics Austria

Citations(all)

35268

Citations(since 2020)

11853

Cited By

28556

hIndex(all)

65

hIndex(since 2020)

44

i10Index(all)

188

i10Index(since 2020)

118

Email

University Profile Page

Google Scholar

Friedrich Leisch Skills & Research Interests

R

statistical computing

biostatistics

cluster analysis

reproducible research

Top articles of Friedrich Leisch

Package ‘tth’

2020/3/19

Friedrich Leisch
Friedrich Leisch

H-Index: 42

Explainable deep learning enhances robust and reliable real‐time monitoring of a chromatographic protein A capture step

Biotechnology Journal

2024/1

Friedrich Leisch
Friedrich Leisch

H-Index: 42

Against the “one method fits all data sets” philosophy for comparison studies in methodological research

Biometrical Journal

2024/1

Friedrich Leisch
Friedrich Leisch

H-Index: 42

Applications of monitoring and tracing the evolution of clustering solutions in dynamic datasets

Journal of Applied Statistics

2023/3/12

Internet

New York: Getting Out and Staying Out.[updated 2015

2015

Monitoring Changes in Clustering Solutions: A Review of Models and Applications

2023/11/3

A white paper on good research practices in benchmarking: The case of cluster analysis

2023/11

Klassisches maschinelles Lernen

2023/9/1

Ursula Laa
Ursula Laa

H-Index: 13

Friedrich Leisch
Friedrich Leisch

H-Index: 42

Glyphosate-Based Herbicide Formulations with Greater Impact on Earthworms and Water Infiltration than Pure Glyphosate

Soil Systems

2023/7/20

Friedrich Leisch
Friedrich Leisch

H-Index: 42

Application of CNN ensembles to model Fourier trans-form infrared spectra

Statistical Computing 2023

2023/7

Friedrich Leisch
Friedrich Leisch

H-Index: 42

Explainable deep learning for improved real-time monitoring of a chromatographic protein A capture step

Authorea Preprints

2023/5/13

Friedrich Leisch
Friedrich Leisch

H-Index: 42

clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets

Plos one

2022/12/15

Muhammad Atif
Muhammad Atif

H-Index: 17

Friedrich Leisch
Friedrich Leisch

H-Index: 42

Reducing overall herbicide use may reduce risks to humans but increase toxic loads to honeybees, earthworms and birds

Environmental Sciences Europe

2022/12

Friedrich Leisch
Friedrich Leisch

H-Index: 42

Package ‘exams’

2022/10/17

Pesticide use and associated greenhouse gas emissions in sugar beet, apples, and viticulture in Austria from 2000 to 2019

Agriculture

2022/6/17

Friedrich Leisch
Friedrich Leisch

H-Index: 42

Effects of glyphosate-based herbicides and their active ingredients on earthworms, water infiltration and glyphosate leaching are influenced by soil properties

Environmental Sciences Europe

2021/12

János Győri
János Győri

H-Index: 0

Friedrich Leisch
Friedrich Leisch

H-Index: 42

The role of unpaid domestic work in explaining the gender gap in the (monetary) value of leisure

Transportation

2021/8/28

See List of Professors in Friedrich Leisch University(Universität für Bodenkultur Wien)

Co-Authors

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