Patrick Mäder

About Patrick Mäder

Patrick Mäder, With an exceptional h-index of 40 and a recent h-index of 28 (since 2020), a distinguished researcher at Technische Universität Ilmenau, specializes in the field of Machine Learning, Data-intensive Systems, Software Engineering, Safety Engineering, Computational Biology.

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

7 Dimensions of software change patterns

Plant macrophenological dynamics-from individuals to plant group behaviour using citizen science data

Leveraging Citizen Science and Machine Learning for Plant Phenology Monitoring

Opportunistic plant observations reveal spatial and temporal gradients in phenology

Recurrent Autoencoder for Weld Discontinuity Prediction

Assessing the utility of text-to-SQL approaches for satisfying software developer information needs

MagneticPillars: Efficient Point Cloud Registration Through Hierarchized Birds-Eye-View Cell Correspondence Refinement

Data-driven estimation of scalar quantities from planar velocity measurements by deep learning applied to temperature in thermal convection

Patrick Mäder Information

University

Position

Prof. Dr.-Ing. (JP) of Computer Science

Citations(all)

5545

Citations(since 2020)

3693

Cited By

2915

hIndex(all)

40

hIndex(since 2020)

28

i10Index(all)

96

i10Index(since 2020)

74

Email

University Profile Page

Google Scholar

Patrick Mäder Skills & Research Interests

Machine Learning

Data-intensive Systems

Software Engineering

Safety Engineering

Computational Biology

Top articles of Patrick Mäder

7 Dimensions of software change patterns

Scientific Reports

2024/3/13

Patrick Mäder
Patrick Mäder

H-Index: 23

Plant macrophenological dynamics-from individuals to plant group behaviour using citizen science data

2024/3/7

Leveraging Citizen Science and Machine Learning for Plant Phenology Monitoring

2024/3/7

Patrick Mäder
Patrick Mäder

H-Index: 23

David Boho
David Boho

H-Index: 5

Opportunistic plant observations reveal spatial and temporal gradients in phenology

npj Biodiversity

2024/3/6

Patrick Mäder
Patrick Mäder

H-Index: 23

David Boho
David Boho

H-Index: 5

Recurrent Autoencoder for Weld Discontinuity Prediction

Journal of Advanced Joining Processes

2024/2/8

Assessing the utility of text-to-SQL approaches for satisfying software developer information needs

Empirical Software Engineering

2024/2

Martin Hofmann
Martin Hofmann

H-Index: 23

Patrick Mäder
Patrick Mäder

H-Index: 23

MagneticPillars: Efficient Point Cloud Registration Through Hierarchized Birds-Eye-View Cell Correspondence Refinement

2024

Patrick Mäder
Patrick Mäder

H-Index: 23

Data-driven estimation of scalar quantities from planar velocity measurements by deep learning applied to temperature in thermal convection

Experiments in Fluids

2023/12

Patrick Mäder
Patrick Mäder

H-Index: 23

Christian Cierpka
Christian Cierpka

H-Index: 21

Bridging the gap: how to adopt opportunistic plant observations for phenology monitoring

Frontiers in Plant Science

2023/10/4

Patrick Mäder
Patrick Mäder

H-Index: 23

David Boho
David Boho

H-Index: 5

Künstliche Intelligenz im Naturschutz

Natur und Landschaft

2023/10

Christian Schneider
Christian Schneider

H-Index: 19

Patrick Mäder
Patrick Mäder

H-Index: 23

Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks

arXiv preprint arXiv:2309.04515

2023/9/8

Patrick Mäder
Patrick Mäder

H-Index: 23

Marco Seeland
Marco Seeland

H-Index: 12

LiDAR-BEVMTN: Real-Time LiDAR Bird's-Eye View Multi-Task Perception Network for Autonomous Driving

arXiv preprint arXiv:2307.08850

2023/7/17

Patrick Mäder
Patrick Mäder

H-Index: 23

Dropout is not all you need to prevent gradient leakage

Proceedings of the AAAI Conference on Artificial Intelligence

2023/6/26

Patrick Mäder
Patrick Mäder

H-Index: 23

Marco Seeland
Marco Seeland

H-Index: 12

A Static Analysis Platform for Investigating Security Trends in Repositories

2023/5/20

Clemens-Alexander Brust
Clemens-Alexander Brust

H-Index: 6

Patrick Mäder
Patrick Mäder

H-Index: 23

FS3change: A Scalable Method for Change Pattern Mining

IEEE Transactions on Software Engineering

2023/4/24

Patrick Mäder
Patrick Mäder

H-Index: 23

Discovering unknown response patterns in progress test data to improve the estimation of student performance

BMC Medical Education

2023/3/29

Patrick Mäder
Patrick Mäder

H-Index: 23

The HAInich: A multidisciplinary vision data-set for a better understanding of the forest ecosystem

Scientific Data

2023/3/27

Inferring the temperature from planar velocity measurements in Rayleigh-Bénard convection by deep learning

2023/3/23

Patrick Mäder
Patrick Mäder

H-Index: 23

Christian Cierpka
Christian Cierpka

H-Index: 21

A systematic comparison of deep learning methods for EEG time series analysis

Frontiers in Neuroinformatics

2023/2/23

Jens Haueisen
Jens Haueisen

H-Index: 26

Patrick Mäder
Patrick Mäder

H-Index: 23

Parameterizing echo state networks for multi-step time series prediction

Neurocomputing

2023/2/14

Karl Worthmann
Karl Worthmann

H-Index: 15

Patrick Mäder
Patrick Mäder

H-Index: 23

See List of Professors in Patrick Mäder University(Technische Universität Ilmenau)

Co-Authors

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