Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
In order to better understand how the brain perceives faces, it is important to know what objective drives learning in the ventral visual stream. To answer this question, we model neural responses to faces in the macaque inferotemporal (IT) cortex with a deep self-supervised generative model, β-VAE,...
Κύριοι συγγραφείς: | Higgins, I, Chang, L, Langston, V, Hassabis, D, Summerfield, C, Tsao, D, Botvinick, M |
---|---|
Μορφή: | Journal article |
Γλώσσα: | English |
Έκδοση: |
Springer Nature
2021
|
Παρόμοια τεκμήρια
-
Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
ανά: Irina Higgins, κ.ά.
Έκδοση: (2021-11-01) -
Shape Similarity, Better than Semantic Membership, Accounts for the Structure of Visual Object Representations in a Population of Monkey Inferotemporal Neurons
ανά: Baldassi, Carlo, κ.ά.
Έκδοση: (2013) -
Visual identification following inferotemporal ablation in the monkey.
ανά: Gaffan, D, κ.ά.
Έκδοση: (1986) -
Disentangling the latent space of GANs for semantic face editing
ανά: Yongjie Niu, κ.ά.
Έκδοση: (2023-01-01) -
Disentangling the latent space of GANs for semantic face editing.
ανά: Yongjie Niu, κ.ά.
Έκδοση: (2023-01-01)