Urs Köster

825 total citations
8 papers, 236 citations indexed

About

Urs Köster is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Statistical and Nonlinear Physics. According to data from OpenAlex, Urs Köster has authored 8 papers receiving a total of 236 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cognitive Neuroscience, 3 papers in Artificial Intelligence and 2 papers in Statistical and Nonlinear Physics. Recurrent topics in Urs Köster's work include Neural dynamics and brain function (4 papers), Visual perception and processing mechanisms (3 papers) and Neural Networks and Applications (2 papers). Urs Köster is often cited by papers focused on Neural dynamics and brain function (4 papers), Visual perception and processing mechanisms (3 papers) and Neural Networks and Applications (2 papers). Urs Köster collaborates with scholars based in United States, Finland and Germany. Urs Köster's co-authors include Aapo Hyvärinen, Bruno A. Olshausen, Charles M. Gray, Jascha Sohl‐Dickstein, Arjun K. Bansal, Marcel Nassar, Amir Khosrowshahi, Evan Archer, Luke Hornof and Jonathan W. Pillow and has published in prestigious journals such as Nature Communications, PLoS Computational Biology and Neural Computation.

In The Last Decade

Urs Köster

8 papers receiving 228 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Urs Köster United States	7	97	80	73	46	35	8	236
Luis G. Sánchez Giraldo United States	7	55 0.6×	79 1.0×	74 1.0×	19 0.4×	16 0.5×	20	208
Mustafa Cem KASAPBAŞI Türkiye	5	208 2.1×	66 0.8×	44 0.6×	49 1.1×	15 0.4×	22	289
Saleh Ashkboos Switzerland	4	37 0.4×	73 0.9×	26 0.4×	18 0.4×	22 0.6×	8	113
Roman Sandler United States	11	114 1.2×	49 0.6×	72 1.0×	29 0.6×	8 0.2×	18	297
Jeanne Rubner Germany	3	80 0.8×	190 2.4×	73 1.0×	99 2.2×	16 0.5×	5	276
Anil Kumar Tiwari India	9	178 1.8×	36 0.5×	29 0.4×	45 1.0×	12 0.3×	56	269
Tomoko Ozeki Japan	8	59 0.6×	176 2.2×	38 0.5×	84 1.8×	14 0.4×	18	253
Jean-Pierre Drouhard Canada	8	130 1.3×	48 0.6×	23 0.3×	19 0.4×	35 1.0×	11	383
Tristan J. Webb United Kingdom	7	67 0.7×	51 0.6×	83 1.1×	6 0.1×	28 0.8×	7	170
Luca Versari Italy	9	85 0.9×	50 0.6×	14 0.2×	32 0.7×	24 0.7×	17	172

Countries citing papers authored by Urs Köster

Since Specialization

Citations

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

Fields of papers citing papers by Urs Köster

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Urs Köster

This figure shows the co-authorship network connecting the top 25 collaborators of Urs Köster. A scholar is included among the top collaborators of Urs Köster 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 Urs Köster. Urs Köster is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Burnim, Jacob, et al.. (2024). Scalable spatiotemporal prediction with Bayesian neural fields. Nature Communications. 15(1). 7942–7942. 8 indexed citations

2.

Köster, Urs, et al.. (2019). Online Normalization for Training Neural Networks. arXiv (Cornell University). 32. 8431–8441. 6 indexed citations

3.

Köster, Urs, Tristan J. Webb, Xin Wang, et al.. (2017). Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks. Neural Information Processing Systems. 30. 1742–1752. 76 indexed citations

4.

Köster, Urs, Jascha Sohl‐Dickstein, Charles M. Gray, & Bruno A. Olshausen. (2014). Modeling Higher-Order Correlations within Cortical Microcolumns. PLoS Computational Biology. 10(7). e1003684–e1003684. 37 indexed citations

5.

Archer, Evan, Urs Köster, Jonathan W. Pillow, & Jakob H. Macke. (2014). Low-dimensional models of neural population activity in sensory cortical circuits. Max Planck Digital Library. 27. 343–351. 20 indexed citations

6.

Köster, Urs & Aapo Hyvärinen. (2010). A Two-Layer Model of Natural Stimuli Estimated with Score Matching. Neural Computation. 22(9). 2308–2333. 17 indexed citations

7.

Hyvärinen, Aapo & Urs Köster. (2007). Complex cell pooling and the statistics of natural images. Network Computation in Neural Systems. 18(2). 81–100. 42 indexed citations

8.

Hyvärinen, Aapo & Urs Köster. (2006). FastISA: A fast fixed-point algorithm for Independent Subspace Analysis. The European Symposium on Artificial Neural Networks. 371–376. 30 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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