Predicting population neural activity in the Algonauts challenge using end-to-end trained Siamese networks and group convolutions

Georgin Jacob; Harish Katti

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arXiv · 2001.05841

Predicting population neural activity in the Algonauts challenge using end-to-end trained Siamese networks and group convolutions

Georgin Jacob·Harish Katti

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Abstract

The Algonauts challenge is about predicting the object representations in the form of Representational Dissimilarity Matrices (RDMS) derived from visual brain regions. We used a customized deep learning model using the concept of Siamese networks and group convolutions to predict neural distances corresponding to a pair of images. Training data was best explained by distances computed over the last layer.

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BibTeX RIS

Georgin Jacob, Harish Katti. 2020-01-13. Predicting population neural activity in the Algonauts challenge using end-to-end trained Siamese networks and group convolutions. https://arxiv.org/abs/2001.05841

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