Fabian H. Sinz

4.5k citations
31 papers · 2.0k indexed · 1 hit paper · h-index 17
Topics
Neural dynamics and brain function (14 papers)Visual perception and processing mechanisms (8 papers)Blind Source Separation Techniques (6 papers)

In The Last Decade

Fabian H. Sinz

31 papers receiving 2.0k citations

Hit Papers

Principles of connectivity among morphologically defined ...20152026201820222015100200300400500

Peers

Fabian H. Sinz
Comparison fields: 5 of 129
  • Cognitive Neuroscience 827
  • Artificial Intelligence 704
  • Cellular and Molecular Neuroscience 558
  • Computer Vision and Pattern Recognition 494
  • Molecular Biology 286
Replace Daniel Soudry with:
Daniel Soudry Israel
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Fabian H. Sinz relative to Daniel Soudry Israel Daniel Soudry's profile →
Citations per field
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Citations per year

Countries citing papers authored by Fabian H. Sinz

Since Specialization
Citations

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

Fields of papers citing papers by Fabian H. Sinz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fabian H. Sinz. 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 Fabian H. Sinz. The network helps show where Fabian H. Sinz may publish in the future.

Co-authorship network of co-authors of Fabian H. Sinz

This figure shows the co-authorship network connecting the top 25 collaborators of Fabian H. Sinz. A scholar is included among the top collaborators of Fabian H. Sinz 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 Fabian H. Sinz. Fabian H. Sinz 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
#WorkIndexed citations
1 1
2 6
3 9
4 26
5 32
6 4
7 92
8 103
9
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
2
10 113
11 15
12 9
13
Hierarchical Modeling of Local Image Features through L_p-Nested Symmetric Distributions
17
14 48
15
The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction
10
16 16
17
An Analysis of Inference with the Universum
66
18 254
19
Large Scale Transductive SVMs
355
20 141

About Fabian H. Sinz

Fabian H. Sinz is a scholar working on Cognitive Neuroscience, Biophysics and Signal Processing, having authored 31 papers that have together received 2.0k indexed citations. Recurring topics across this work include Neural dynamics and brain function (14 papers), Visual perception and processing mechanisms (8 papers) and Blind Source Separation Techniques (6 papers). The work is most often cited by research in Cognitive Neuroscience (827 citations), Cellular and Molecular Neuroscience (558 citations) and Computer Vision and Pattern Recognition (494 citations). Fabian H. Sinz has collaborated with scholars based in Germany, United States and Canada. Frequent co-authors include Léon Bottou, Ronan Collobert, Jason Weston, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker, Philipp Berens, Xiaolong Jiang, Cathryn R. Cadwell and Saumil S. Patel. Their work appears in journals such as Nature, Science and Nature Communications.

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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