Simon Kornblith

15.2k citations
29 papers · 2.4k indexed · 3 hit papers · h-index 19

Simon Kornblith

28 papers receiving 2.4k citations

Hit Papers

Robust fine-tuning of zero-shot models2082019202620212023200400600

Peers

Simon Kornblith
Comparison fields: 5 of 159
  • Cognitive Neuroscience 785
  • Computer Vision and Pattern Recognition 766
  • Health Informatics 44
  • Artificial Intelligence 914
  • Radiology, Nuclear Medicine and Imaging 353
Replace Neil C. Rabinowitz with:
Neil C. Rabinowitz United Kingdom
Erhardt Barth Germany
Wieland Brendel Germany
Huiguang He China
Charles F. Cadieu United States
Ha Hong United States
Paul Sajda United States
Dimitris Samaras United States
Bin Yan China
Mohammed Yeasin United States
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Citations per field
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Citations per year

Countries citing papers authored by Simon Kornblith

Since Specialization
Citations

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

Fields of papers citing papers by Simon Kornblith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20248
3 202343
4 20236
5 202223
6 202290
7
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
202152
8 202130
9
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks
20207
10
Saccader: Improving Accuracy of Hard Attention Models for Vision
20195
11
When does label smoothing help
201970
12
Exploring the Origins and Prevalence of Texture Bias in Convolutional Neural Networks.
20194
13 2018180
14 201786
15 201713
16 201565
17 201422
18 2013100
19 2011124
20 2008162

About Simon Kornblith

Simon Kornblith is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Artificial Intelligence, having authored 29 papers that have together received 2.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (10 papers), Advanced Neural Network Applications (10 papers), Domain Adaptation and Few-Shot Learning (9 papers), Memory and Neural Mechanisms (6 papers), Multimodal Machine Learning Applications (5 papers), Visual perception and processing mechanisms (4 papers), Face Recognition and Perception (3 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Cognitive Neuroscience (785 citations), Computer Vision and Pattern Recognition (766 citations) and Health Informatics (44 citations). Simon Kornblith has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Quoc V. Le, Jonathon Shlens, Earl K. Miller, Itzhak Fried, Christof Koch, Rodrigo Quian Quiroga, Florian Mormann, Mikael Lundqvist, Mohammad Norouzi and Alexander Kraskov. Their work appears in journals such as Neuron, Proceedings of the National Academy of Sciences, Journal of Neuroscience, Current Biology and Nature Neuroscience.

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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