Robert Geirhos

4.6k citations
12 papers · 1.2k indexed · 1 hit paper · h-index 5
Topics
Face Recognition and Perception (5 papers)Visual Attention and Saliency Detection (5 papers)Visual perception and processing mechanisms (2 papers)

In The Last Decade

Robert Geirhos

11 papers receiving 1.1k citations

Hit Papers

Shortcut learning in deep neural networks20202026202220242020250500750

Peers

Robert Geirhos
Comparison fields: 5 of 132
  • Artificial Intelligence 623
  • Computer Vision and Pattern Recognition 410
  • Cognitive Neuroscience 151
  • Radiology, Nuclear Medicine and Imaging 125
  • Health Informatics 62
Replace Claudio Michaelis with:
Claudio Michaelis Germany
Jörn-Henrik Jacobsen Canada
Jose L. Part United Kingdom
Wieland Brendel Germany
Chaofan Chen China
Sirui Ding China
Zifan Wang United States
Piotr Mardziel United States
Brandon Rothrock United States
Robert Geirhos relative to Claudio Michaelis Germany Claudio Michaelis's profile →
Citations per field
00.5×1.5×
Claudio Michaelis · 1×
Citations per year

Countries citing papers authored by Robert Geirhos

Since Specialization
Citations

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

Fields of papers citing papers by Robert Geirhos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Geirhos

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1 14
2 28
3 0
4 1
5 2
6
Shortcut learning in deep neural networksbreakdown →
833
7 2
8
Natural Images are More Informative for Interpreting CNN Activations than State-of-the-Art Synthetic Feature Visualizations
1
9 3
10 265
11 1
12 14

About Robert Geirhos

Robert Geirhos is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Biophysics, having authored 12 papers that have together received 1.2k indexed citations. Recurring topics across this work include Face Recognition and Perception (5 papers), Visual Attention and Saliency Detection (5 papers) and Visual perception and processing mechanisms (2 papers). The work is most often cited by research in Health Informatics (62 citations), Computer Vision and Pattern Recognition (410 citations) and Artificial Intelligence (623 citations). Robert Geirhos has collaborated with scholars based in Germany, Switzerland and United Kingdom. Frequent co-authors include Felix A. Wichmann, Matthias Bethge, Claudio Michaelis, Wieland Brendel, Jörn-Henrik Jacobsen, Richard S. Zemel, Heiko H. Schütt, Marianne Maertens, Jonas Rauber and R. Zimmermann. Their work appears in journals such as Journal of Vision, Nature Machine Intelligence and Annual Review of Vision Science.

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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