Gerold Baier

2.6k citations
105 papers · 2.0k · h-index 26

Impact in

Papers in

Gerold Baier

101 papers receiving 1.9k citations

Peers

Gerold Baier
Comparison fields: 5 of 129
  • Cognitive Neuroscience 985
  • Statistical and Nonlinear Physics 559
  • Urology 110
  • Computer Networks and Communications 439
  • Cellular and Molecular Neuroscience 335
Replace Marc Goodfellow with:
Marc Goodfellow United Kingdom
Paul So United States
W.G. Gibson Australia
C. J. Pérez Vicente Spain
Gil Bub United Kingdom
David Golomb Israel
Alvin Shrier Canada
Bruce W. Knight United States
Р. Р. Алиев Russia
Dmitry E. Postnov Russia
Gerold Baier relative to Marc Goodfellow United Kingdom Marc Goodfellow's profile →
Citations per field
00.5×4.8×
Marc Goodfellow · 1×
Citations per year

Countries citing papers authored by Gerold Baier

Since Specialization
Citations

This map shows the geographic impact of Gerold Baier'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 Gerold Baier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gerold Baier more than expected).

Fields of papers citing papers by Gerold Baier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gerold Baier. 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 Gerold Baier. The network helps show where Gerold Baier may publish in the future.

Co-authors

The 25 scholars most cited alongside Gerold Baier, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gerold Baier Line = papers co-authored together Gerold Baier links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000152
2 1990108
3 201488
4 200588
5 201386
6 201185
7 199560
8 201058
9 201157
10 201151
11 201250
12 200749
13 201245
14 200543
15 201440
16 201237
17 201035
18 200634
19 200229
20 199129

About Gerold Baier

Gerold Baier is a scholar working on Cognitive Neuroscience, Computer Networks and Communications, Statistical and Nonlinear Physics, Molecular Biology and Cellular and Molecular Neuroscience, having authored 105 papers that have together received 2.0k indexed citations. Recurring topics across this work include Neural dynamics and brain function (44 papers), Nonlinear Dynamics and Pattern Formation (37 papers), Chaos control and synchronization (18 papers), EEG and Brain-Computer Interfaces (18 papers), stochastic dynamics and bifurcation (15 papers), Mathematical Dynamics and Fractals (11 papers), Quantum chaos and dynamical systems (10 papers) and Complex Systems and Time Series Analysis (10 papers). The work is most often cited by research in Cognitive Neuroscience (985 citations), Statistical and Nonlinear Physics (559 citations), Urology (110 citations), Computer Networks and Communications (439 citations) and Cellular and Molecular Neuroscience (335 citations). Gerold Baier has collaborated with scholars based in Germany, United Kingdom and Mexico. Frequent co-authors include Marc Goodfellow, Peter N. Taylor, Markus Müller, Ulrich Stephani, Yujiang Wang, Kaspar Schindler, Sven Sahle, Thomas Hermann, Ursula Kummer and Christian Rummel. Their work appears in journals such as Physics Letters A, Europhysics Letters (EPL), Chaos Solitons & Fractals, Chaos An Interdisciplinary Journal of Nonlinear Science and The Journal of Chemical Physics.

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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