Jonathon Shlens

40.2k citations
34 papers · 5.4k indexed · 6 hit papers · h-index 22

Jonathon Shlens

33 papers receiving 5.2k citations

Hit Papers

Large Scale Interactiv...30020082026201420202505007501000

Peers

Jonathon Shlens
Comparison fields: 5 of 164
  • Cognitive Neuroscience 2.0k
  • Computer Vision and Pattern Recognition 2.0k
  • Cellular and Molecular Neuroscience 1.3k
  • Artificial Intelligence 1.5k
  • Statistical and Nonlinear Physics 337
Replace Helge Ritter with:
Helge Ritter Germany
Claudia Clopath United Kingdom
Biswa Sengupta United Kingdom
Alexander S. Ecker Germany
Jost Tobias Springenberg Germany
Malte J. Rasch United States
Ning Qian United States
Lei Deng China
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Citations per field
00.5×2.7×
Helge Ritter · 1×
Citations per year

Countries citing papers authored by Jonathon Shlens

Since Specialization
Citations

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

Fields of papers citing papers by Jonathon Shlens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20233
2 20237
3
Revisiting ResNets: Improved Training and Scaling Strategies
20212
4 20215
5
Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.
20202
6
Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation
20205
7 201395
8 201272
9 201172
10 201050
11
Functional Identification of Individual Cones in the Receptive Fields of Primate Retinal Ganglion Cells
20091
12 2009104
13 200976
14 200986
15
Light Adaptation Changes the Size of Receptive Fields in Seven Distinct Primate Retinal Ganglion Cell Types
20081
16 200858
17 2007134
18 2007111
19 2006326
20 200563

About Jonathon Shlens

Jonathon Shlens is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition, having authored 34 papers that have together received 5.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (17 papers), Retinal Development and Disorders (12 papers), Photoreceptor and optogenetics research (10 papers), Advanced Neural Network Applications (7 papers), Visual perception and processing mechanisms (6 papers), Neuroscience and Neural Engineering (6 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Cognitive Neuroscience (2.0k citations), Computer Vision and Pattern Recognition (2.0k citations) and Cellular and Molecular Neuroscience (1.3k citations). Jonathon Shlens has collaborated with scholars based in United States, United Kingdom and Poland. Frequent co-authors include Augustus Odena, Christopher Olah, E. J. Chichilnisky, A. M. Litke, Alexander Sher, Simon Kornblith, Quoc V. Le, Eero P. Simoncelli, Jonathan W. Pillow and Liam Paninski. Their work appears in journals such as Journal of Neuroscience, Nature, Neural Computation, Investigative Ophthalmology & Visual 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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