Author

Jonathan Prescott-Roy

Massachusetts Institute of Technology

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Neuroscience· 1

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Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Organism:human· 1 Organism:non-human primate· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Daniel L. K. YaminsiD· 1 shared Elias B. IssaiD· 1 shared Franziska Geiger· 1 shared Ha HongiD· 1 shared James J. DiCarloiD· 1 shared Jonas KubiliusiD· 1 shared Kailyn SchmidtiD· 1 shared Kohitij KariD· 1 shared

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2020-2020 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperNeuroscience

Daniel L. K. YaminsORCID

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1 paper

Recent·Most cited

Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?

Martin Schrimpf, Jonas Kubilius, Ha Hong, Najib J. Majaj, Rishi Rajalingham, Elias B. Issa, Kohitij Kar, Pouya Bashivan, Jonathan Prescott-Roy, Franziska Geiger, Kailyn Schmidt, Daniel L. K. Yamins, James J. DiCarlo

Among dozens of ImageNet-trained networks scored against macaque V4/IT recordings and human behavior, DenseNet-169, CORnet-S and ResNet-101 rank highest, and brain similarity stops tracking accuracy above 70% top-1.

bioRxiv · Jan 2, 2020 · PreprintNeuroscience✦ In-depth digest