Geometric characterization in more network variants.

<p>Two additional network geometries have been estimated: ResNet50 trained with contrastive learning (trained weights were obtained from <a href="https://github.com/AndrewAtanov/simclr-pytorch" target="_blank">https://github.com/AndrewAtanov/simclr-pytorch</a>)...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ghislain St-Yves (22238830) (author)
مؤلفون آخرون:	Kendrick Kay (7901603) (author), Thomas Naselaris (103861) (author)
منشور في:	2025
الموضوعات:	Neuroscience Biotechnology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified large fmri dataset g ., objects deep neural networks support accurate classification shot classification performance single geometric property simple &# 8220 shot &# 8221 brain area depends brain activity patterns estimated geometric properties accurate linear classification mid dnn layers concept manifolds differs geometric properties linear classification dnn layers &# 8217 concept manifolds linear classifiers visual cortex vice versa scenes ). recent theory negatively correlated even though encode images effective number directly determine
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Geometric characterization in more network variants.

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