Wolfgang Mader

1.1k total citations
23 papers, 748 citations indexed

About

Wolfgang Mader is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Cellular and Molecular Neuroscience. According to data from OpenAlex, Wolfgang Mader has authored 23 papers receiving a total of 748 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cognitive Neuroscience, 6 papers in Artificial Intelligence and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Wolfgang Mader's work include Neural dynamics and brain function (7 papers), Functional Brain Connectivity Studies (4 papers) and Neurobiology and Insect Physiology Research (3 papers). Wolfgang Mader is often cited by papers focused on Neural dynamics and brain function (7 papers), Functional Brain Connectivity Studies (4 papers) and Neurobiology and Insect Physiology Research (3 papers). Wolfgang Mader collaborates with scholars based in Germany, United Kingdom and United States. Wolfgang Mader's co-authors include Jens Timmer, Björn Schelter, Dorothee Saur, K.-P. Hoffmann, R.G. Erickson, C. Distler, Cornelius Weiller, Harald Wolf, Volkmar Glauche and Rüdiger Lange and has published in prestigious journals such as Bioinformatics, NeuroImage and Scientific Reports.

In The Last Decade

Wolfgang Mader

23 papers receiving 735 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Wolfgang Mader Germany 11 384 192 108 106 85 23 748
Robert A. A. Campbell United States 19 316 0.8× 188 1.0× 11 0.1× 56 0.5× 407 4.8× 36 1.1k
Alberto Labarga Spain 19 519 1.4× 437 2.3× 23 0.2× 14 0.1× 180 2.1× 26 1.3k
Roland E. Suri Switzerland 12 611 1.6× 153 0.8× 24 0.2× 40 0.4× 336 4.0× 25 882
Jeffrey S. Grethe United States 23 588 1.5× 717 3.7× 23 0.2× 168 1.6× 89 1.0× 68 1.8k
Benjamin Griffiths United Kingdom 14 447 1.2× 21 0.1× 21 0.2× 17 0.2× 114 1.3× 37 663
Kei Majima Japan 11 391 1.0× 41 0.2× 11 0.1× 23 0.2× 127 1.5× 27 570
Ke Zeng China 24 387 1.0× 246 1.3× 7 0.1× 170 1.6× 108 1.3× 59 1.5k
Jun-Yun Zhang China 12 887 2.3× 105 0.5× 62 0.6× 38 0.4× 98 1.2× 21 978
Adi Maron‐Katz Israel 15 380 1.0× 515 2.7× 6 0.1× 51 0.5× 29 0.3× 21 1.2k
Rocío Romero‐Zaliz Spain 16 83 0.2× 126 0.7× 34 0.3× 19 0.2× 137 1.6× 36 819

Countries citing papers authored by Wolfgang Mader

Since Specialization
Citations

This map shows the geographic impact of Wolfgang Mader's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wolfgang Mader with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wolfgang Mader more than expected).

Fields of papers citing papers by Wolfgang Mader

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wolfgang Mader. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wolfgang Mader. The network helps show where Wolfgang Mader may publish in the future.

Co-authorship network of co-authors of Wolfgang Mader

This figure shows the co-authorship network connecting the top 25 collaborators of Wolfgang Mader. A scholar is included among the top collaborators of Wolfgang Mader based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Wolfgang Mader. Wolfgang Mader is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mader, Wolfgang, et al.. (2023). Convolutional Transformer Fusion Blocks for Multi-Modal Gesture Recognition. IEEE Access. 11. 34094–34103. 9 indexed citations
2.
Mader, Wolfgang, et al.. (2020). Depthwise Separable Temporal Convolutional Network for Action Segmentation. 633–641. 4 indexed citations
3.
Kaschek, Daniel, Wolfgang Mader, M. Fehling–Kaschek, Marcus Rosenblatt, & Jens Timmer. (2019). Dynamic Modeling, Parameter Estimation, and Uncertainty Analysis in R. Journal of Statistical Software. 88(10). 19 indexed citations
4.
Mader, Wolfgang, Malenka Mader, Jens Timmer, Marco Thiel, & Björn Schelter. (2015). Networks: On the relation of bi- and multivariate measures. Scientific Reports. 5(1). 10805–10805. 11 indexed citations
5.
Raue, Andreas, Bernhard Steiert, Max Schelker, et al.. (2015). Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems. Bioinformatics. 31(21). 3558–3560. 153 indexed citations
6.
Mader, Malenka, Wolfgang Mader, Jens Timmer, et al.. (2014). Optimized spectral estimation for nonlinear synchronizing systems. Physical Review E. 89(3). 32912–32912. 3 indexed citations
7.
Thiel, Marco, Malenka Mader, Wolfgang Mader, et al.. (2014). Assessing the strength of directed influences among neural signals: An approach to noisy data. Journal of Neuroscience Methods. 239. 47–64. 17 indexed citations
8.
Schelter, Björn, Malenka Mader, Wolfgang Mader, et al.. (2014). Overarching framework for data-based modelling. Europhysics Letters (EPL). 105(3). 30004–30004. 14 indexed citations
9.
Mader, Malenka, Wolfgang Mader, Bruce J. Gluckman, Jens Timmer, & Björn Schelter. (2014). Statistical evaluation of forecasts. Physical Review E. 90(2). 22133–22133. 2 indexed citations
10.
Vives‐Gilabert, Yolanda, Ahmed Abdulkadir, Christoph P. Kaller, et al.. (2013). Detection of preclinical neural dysfunction from functional connectivity graphs derived from task fMRI. An example from degeneration. Psychiatry Research Neuroimaging. 214(3). 322–330. 5 indexed citations
11.
Mader, Malenka, et al.. (2013). Block-bootstrapping for noisy data. Journal of Neuroscience Methods. 219(2). 285–291. 10 indexed citations
12.
Diehl, Florian, et al.. (2012). The Stomatogastric Nervous System as a Model for Studying Sensorimotor Interactions in Real-Time Closed-Loop Conditions. Frontiers in Computational Neuroscience. 6. 13–13. 8 indexed citations
13.
Mader, Wolfgang, et al.. (2012). Inference of time-dependent causal influences in Networks. Biomedizinische Technik/Biomedical Engineering. 57(SI-1 Track-F). 2 indexed citations
14.
Ouden, Dirk‐Bart den, Dorothee Saur, Wolfgang Mader, et al.. (2011). Network modulation during complex syntactic processing. NeuroImage. 59(1). 815–823. 84 indexed citations
15.
Alfons, Andreas, et al.. (2010). Robust variable selection with application to quality of life research. Statistical Methods & Applications. 20(1). 65–82. 6 indexed citations
16.
Saur, Dorothee, Björn Schelter, Susanne Schnell, et al.. (2009). Combining functional and anatomical connectivity reveals brain networks for auditory language comprehension. NeuroImage. 49(4). 3187–3197. 206 indexed citations
17.
Schelter, B., et al.. (2009). Inference of causal interactions in fMRI data: The challenge of slice timing. NeuroImage. 47. S124–S124. 1 indexed citations
18.
Stein, Wolfgang, et al.. (2008). Motor pattern selection by combinatorial code of interneuronal pathways. Journal of Computational Neuroscience. 25(3). 543–561. 9 indexed citations
19.
Wolf, Harald, et al.. (2005). The insecticide pymetrozine selectively affects chordotonal mechanoreceptors. Journal of Experimental Biology. 208(23). 4451–4466. 62 indexed citations
20.
Hoffmann, K.-P., C. Distler, R.G. Erickson, & Wolfgang Mader. (1988). Physiological and anatomical identification of the nucleus of the optic tract and dorsal terminal nucleus of the accessory optic tract in monkeys. Experimental Brain Research. 69(3). 635–44. 87 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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