Daniel Yamins

13.1k citations
63 papers · 4.8k · 3 hit papers · h-index 21

Impact in

Papers in

    • Neural dynamics and brain function 23
    • Face Recognition and Perception 22
    • Visual perception and processing mechanisms 19
    • Functional Brain Connectivity Studies 4
    • Visual Attention and Saliency Detection 13
    • Multimodal Machine Learning Applications 6
    • Human Pose and Action Recognition 4

Daniel Yamins

61 papers receiving 4.7k citations

Daniel Yamins's Hit Papers

Using goal-driven deep learning models to understand sensory cortex 2016 · 842 citations
8420+4+8Years since publication2505007501000

Peers

Daniel Yamins
Comparison fields: 5 of 176
  • Cognitive Neuroscience 2.6k
  • Computer Vision and Pattern Recognition 1.2k
  • Artificial Intelligence 1.1k
  • Biophysics 202
  • Experimental and Cognitive Psychology 195
Replace Marcel van Gerven with:
Marcel van Gerven Netherlands
Tai Sing Lee United States
Ning Qian United States
Nigel Goddard United Kingdom
Jagath C. Rajapakse Singapore
Malte J. Rasch United States
Jonathon Shlens United States
Felix A. Wichmann Germany
Helge Ritter Germany
Bertram E. Shi Hong Kong
Daniel Yamins relative to Marcel van Gerven Netherlands Marcel van Gerven's profile →
Citations per field
00.5×1.5×1.9×
Marcel van Gerven · 1×
Citations per year

Countries citing papers authored by Daniel Yamins

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Yamins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Performance-optimized hierarchical models predict neural responses in higher visual cortex
Hit paper breakdown →
20141027
2
Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures
Hit paper breakdown →
2013949
3
Using goal-driven deep learning models to understand sensory cortex
Hit paper breakdown →
2016842
4 2014397
5 2018276
6 2019217
7 2016210
8 2021175
9
Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream
201361
10 200355
11 200553
12 200348
13 201838
14
Flexible neural representation for physics prediction
201835
15 201935
16 202031
17 202131
18 201625
19 201923
20 200822

About Daniel Yamins

Daniel Yamins is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition, Artificial Intelligence, Mechanical Engineering and Computer Networks and Communications, having authored 63 papers that have together received 4.8k indexed citations. Recurring topics across this work include Neural dynamics and brain function (23 papers), Face Recognition and Perception (22 papers), Visual perception and processing mechanisms (19 papers), Visual Attention and Saliency Detection (13 papers), Multimodal Machine Learning Applications (6 papers), Human Pose and Action Recognition (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Functional Brain Connectivity Studies (4 papers). The work is most often cited by research in Cognitive Neuroscience (2.6k citations), Computer Vision and Pattern Recognition (1.2k citations), Artificial Intelligence (1.1k citations), Biophysics (202 citations) and Experimental and Cognitive Psychology (195 citations). Daniel Yamins has collaborated with scholars based in United States, China and Belgium. Frequent co-authors include James J. DiCarlo, David Cox, James Bergstra, Ha Hong, Charles F. Cadieu, Ethan A. Solomon, Chengxu Zhuang, Najib J. Majaj, Alex Zhai and Josh H. McDermott. Their work appears in journals such as Journal of Vision, Neuron, Proceedings of the National Academy of Sciences, Cognitive Science and Cognitive Systems Research.

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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