Klaus Obermayer

3.2k total citations
85 papers, 1.7k citations indexed

About

Klaus Obermayer is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Klaus Obermayer has authored 85 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computer Vision and Pattern Recognition, 38 papers in Artificial Intelligence and 22 papers in Signal Processing. Recurrent topics in Klaus Obermayer's work include Neural Networks and Applications (19 papers), Neural dynamics and brain function (10 papers) and Face and Expression Recognition (9 papers). Klaus Obermayer is often cited by papers focused on Neural Networks and Applications (19 papers), Neural dynamics and brain function (10 papers) and Face and Expression Recognition (9 papers). Klaus Obermayer collaborates with scholars based in Germany, United States and United Kingdom. Klaus Obermayer's co-authors include Sambu Seo, Thore Graepel, Klaus Schulten, Ed Erwin, Michael Scholz, Stephan Schmitt, Jan Felix Evers, Carsten Duch, Ralf Herbrich and Helge Ritter and has published in prestigious journals such as NeuroImage, Philosophical Transactions of the Royal Society B Biological Sciences and Biophysical Journal.

In The Last Decade

Klaus Obermayer

80 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Klaus Obermayer Germany 20 859 594 270 246 179 85 1.7k
Ralph Linsker United States 18 979 1.1× 376 0.6× 303 1.1× 678 2.8× 175 1.0× 26 2.0k
Li Deng China 14 2.0k 2.4× 964 1.6× 414 1.5× 175 0.7× 71 0.4× 43 3.3k
Tao Xiong United States 16 572 0.7× 493 0.8× 181 0.7× 192 0.8× 134 0.7× 40 1.5k
Yasemin Altün United States 21 2.4k 2.8× 1.3k 2.2× 354 1.3× 390 1.6× 314 1.8× 41 3.8k
Mikel Luján United Kingdom 22 666 0.8× 450 0.8× 132 0.5× 154 0.6× 184 1.0× 148 2.2k
Thomas Navin Lal Germany 7 1.5k 1.7× 1.3k 2.3× 259 1.0× 341 1.4× 226 1.3× 10 2.9k
Humberto Sossa Mexico 24 712 0.8× 795 1.3× 117 0.4× 201 0.8× 48 0.3× 190 2.0k
Gal Chechik Israel 31 1.2k 1.4× 1.4k 2.3× 308 1.1× 790 3.2× 568 3.2× 106 3.7k
Á. Rodríguez‐Vázquez Spain 36 1.2k 1.4× 625 1.1× 88 0.3× 388 1.6× 74 0.4× 450 5.2k
S. Ramakrishnan United States 22 541 0.6× 620 1.0× 338 1.3× 226 0.9× 184 1.0× 199 2.0k

Countries citing papers authored by Klaus Obermayer

Since Specialization
Citations

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

Fields of papers citing papers by Klaus Obermayer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Klaus Obermayer

This figure shows the co-authorship network connecting the top 25 collaborators of Klaus Obermayer. A scholar is included among the top collaborators of Klaus Obermayer 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 Klaus Obermayer. Klaus Obermayer 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
2.
Meyer, Robert K. & Klaus Obermayer. (2016). pypet: A Python Toolkit for Data Management of Parameter Explorations. Frontiers in Neuroinformatics. 10. 38–38. 14 indexed citations
3.
Böhmer, Wendelin, et al.. (2013). Construction of approximation spaces for reinforcement learning. Journal of Machine Learning Research. 14(1). 2067–2118. 7 indexed citations
4.
Obermayer, Klaus, et al.. (2011). Tripartite community structure in social bookmarking data. New Review of Hypermedia and Multimedia. 17(3). 267–294. 2 indexed citations
5.
Murfi, Hendri & Klaus Obermayer. (2009). A two-level learning hierarchy of concept based keyword extraction for tag recommendations. 497. 201–214. 10 indexed citations
6.
Obermayer, Klaus, et al.. (2008). Active Learning by Spherical Subdivision. Journal of Machine Learning Research. 9(5). 105–130. 2 indexed citations
7.
Adiloğlu, Kamil, et al.. (2007). Classification Schemes for Step Sounds Based on Gammatone-Filters. Neural Information Processing Systems. 1 indexed citations
8.
Vollgraf, Roland & Klaus Obermayer. (2006). Sparse Optimization for Second Order Kernel Methods. The 2006 IEEE International Joint Conference on Neural Network Proceedings. 15. 145–152. 5 indexed citations
9.
Adiloğlu, Kamil & Klaus Obermayer. (2005). FINDING SUBSEQUENCES OF MELODIES IN MUSICAL PIECES. The Journal of the Abraham Lincoln Association. 2005. 1 indexed citations
10.
Purwins, H.‐G., Benjamin Blankertz, Klaus Obermayer, & Guido Dornhege. (2004). Scale Degree Profiles from Audio Investigated with Machine Learning. Journal of the Audio Engineering Society. 4 indexed citations
11.
Girard, Agathe, et al.. (2003). Multiple-step ahead prediction for non linear dynamic systems: A Gaussian Process treatment with propagation of the uncertainty. Neural Information Processing Systems. 529–536. 32 indexed citations
12.
Purwins, H.‐G., Benjamin Blankertz, & Klaus Obermayer. (2001). Constant Q Profiles for Tracking Modulations in Audio Data Format. The Journal of the Abraham Lincoln Association. 2001. 1 indexed citations
13.
Blankertz, Benjamin, et al.. (2001). Constant Q Profiles for Tracking Modulations in Audio Data. International Computer Music Conference. 10 indexed citations
14.
Obermayer, Klaus & Terrence J. Sejnowski. (2001). Self-Organizing Map Formation: Foundations of Neural Computation. MIT Press eBooks. 15 indexed citations
15.
Seo, Sambu, et al.. (2000). Gaussian process regression: active data selection and test point rejection. 241–246 vol.3. 74 indexed citations
16.
17.
Blankertz, Benjamin, et al.. (1999). Toroidal models of inter-key relations in tonal music. Biophysical Journal. 89(6). 3873–83. 3 indexed citations
18.
Graepel, Thore, et al.. (1998). Classification on Pairwise Proximity Data. UCL Discovery (University College London). 11. 438–444. 97 indexed citations
19.
Graepel, Thore, et al.. (1997). An Annealed Self-Organizing Map for Source Channel Coding. UCL Discovery (University College London). 10. 430–436. 5 indexed citations
20.
Weber, Cornelius, Helge Ritter, Jack D. Cowan, & Klaus Obermayer. (1997). Development and regeneration of the retinotectal map in goldfish: a computational study. Philosophical Transactions of the Royal Society B Biological Sciences. 352(1361). 1603–1623. 11 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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