Author

Ha Hong

McGovern Institute for Brain ResearchORCID 0000-0002-3200-1038Unclaimed ORCID profile · follow to get notified of new preprints

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Neuroscience· 3

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Organism:human· 3 Research Focus:benchmarking· 2 Approach:deep learning· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

James J. DiCarloiD· 3 shared Daniel L. K. YaminsiD· 1 shared Daniel Yamins· 1 shared Darren Seibert· 1 shared Diego Ardila· 1 shared Elias B. IssaiD· 1 shared Franziska Geiger· 1 shared Jonas KubiliusiD· 1 shared

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10 top collaborators · 25 mutual co-author links

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3 shared papersNeuroscience

James J. DiCarloORCID

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3 papers

Recent·Most cited

NeuroscienceeLifePeer-reviewedJun 11, 2021

Unsupervised changes in core object recognition behavior are predicted by unsupervised neural plasticity in inferior temporal cortex

Xiaoxuan Jia, Ha Hong, James J. DiCarlo

The paper predicts human behavioral changes in object recognition from unsupervised neural plasticity in IT cortex using a computational model.

15 citations

humanstatistical model

NeurosciencebioRxivPreprintJan 2, 2020

✦ In-depth digest

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

Martin Schrimpf, Jonas Kubilius, Ha Hong…·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.

461 citations

non-human primatehuman

NeurosciencebioRxivPreprintJan 12, 2016

A performance-optimized model of neural responses across the ventral visual stream

Darren Seibert, Daniel Yamins, Diego Ardila…·Justin L. Gardner

This paper builds a deep convolutional neural network optimized for object recognition and shows its hierarchical representations align with human ventral visual stream areas from V1 to LOC.

DOI 10.1101/036475