Wieland Brendel

8.5k citations
44 papers · 1.9k indexed · 2 hit papers · h-index 14

Wieland Brendel

43 papers receiving 1.8k citations

Hit Papers

Shortcut learning in deep neural networks8332016202620192022250500750

Peers

Wieland Brendel
Comparison fields: 5 of 166
  • Health Informatics 68
  • Artificial Intelligence 839
  • Cognitive Neuroscience 503
  • Computer Vision and Pattern Recognition 494
  • Biophysics 55
Replace Leonardo Franco with:
Leonardo Franco Spain
Simon Kornblith United States
Mohammed Yeasin United States
Daniel Neil Switzerland
Shuihua Wang United Kingdom
Erhardt Barth Germany
Eiji Uchibe Japan
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Kim‐Han Thung United States
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Citations per year

Countries citing papers authored by Wieland Brendel

Since Specialization
Citations

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

Fields of papers citing papers by Wieland Brendel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Wieland Brendel, 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 Wieland Brendel Line = papers co-authored together Wieland Brendel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 202312
3
Increasing the robustness of DNNs against image corruptions by playing the Game of Noise
202016
4
Improving robustness against common corruptions by covariate shift adaptation
20209
5
Shortcut learning in deep neural networksbreakdown →
2020833
6 202027
7
Accurate, reliable and fast robustness evaluation
201922
8
Robust Perception through Analysis by Synthesis.
20186
9 201811
10 20183
11
What does it take to generate natural textures
201711
12
Demixed principal component analysis of neural population databreakdown →
2016311
13
Unsupervised learning of an efficient short-term memory network
20149
14
Demixed Principal Component Analysis
201132
15 19842
16
[Absorption of a proteolytic enzyme originating from plants out of the gastro-intestinal tract into blood and lymph of rats (author's transl)].
197923
17
[Radioactive microsphere studies of stomach wall blood flow in dogs following truncular vagotomy].
19772
18 197328
19 19683
20 196610

About Wieland Brendel

Wieland Brendel is a scholar working on Health Informatics, Cognitive Neuroscience and Artificial Intelligence, having authored 44 papers that have together received 1.9k indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (11 papers), Neural dynamics and brain function (5 papers), Face Recognition and Perception (4 papers), Visual Attention and Saliency Detection (3 papers), Integrated Circuits and Semiconductor Failure Analysis (3 papers), COVID-19 diagnosis using AI (3 papers), Neural Networks and Applications (3 papers) and Advanced Memory and Neural Computing (2 papers). The work is most often cited by research in Health Informatics (68 citations), Artificial Intelligence (839 citations) and Cognitive Neuroscience (503 citations). Wieland Brendel has collaborated with scholars based in Germany, United States and Portugal. Frequent co-authors include Matthias Bethge, Claudio Michaelis, Felix A. Wichmann, Robert Geirhos, Jörn-Henrik Jacobsen, Richard S. Zemel, Christian K. Machens, Ranulfo Romo, Jonas Rauber and Ádám Kepecs. Their work appears in journals such as Scientific Reports, Transplantation and eLife.

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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