Yoon Lab @ Hanyang

Yoon Lab @ Hanyang

Neuro-inspired AI group

Our group is interested in understanding principles that underlie learning and inference in the brain and machines, mainly by using tools from machine learning and statistics.


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Image by KiJung Yoon

Inference in probabilistic graphical models by graph neural networks
Yoon, KJ., Liao, R., Xiong, Y., Zhang, L., Fetaya, E., Urtasun, R., Zemel, R., & Pitkow, X.
arXiv:1803.07710 (2018)

ICML (2019), Workshop on Tractable Probabilistic Modeling (Best Paper Award)

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Image by Xaq Pitkow

Reviving and improving recurrent backpropagation
Liao, R., Xiong, Y., Fetaya, E., Zhang, L., Yoon, KJ., Pitkow, X., Urtasun, R., & Zemel, R.
ICML (2018) [pdf]

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Image by Yi Gu

A map-like micro-organization of grid cells in the medial entorhinal cortex
Gu, Y., Lewallen, S., Kinkhabwala, A. A., Domnisoru, C., Yoon, KJ., Gauthier, J., Fiete, I. R., and Tank, D. W.
Cell (2018) [pdf]

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Image by KiJung Yoon

Grid cell responses in 1D environments assessed as slices through a 2D lattice
Yoon, KJ.*, Lewallen, S.*, Kinkhabwala, A. A., Tank, D. W., and Fiete, I. R.
Neuron (2016) [pdf],[SI]

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Image by KiJung Yoon

Specific evidence of low-dimensional continuous attractor dynamics in grid cells
Yoon, KJ., Buice, M. A., Barry, C., Hayman, R., Burgess, N., and Fiete, I. R.
Nature Neuroscience (2013)

Conference abstracts

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