A Parameter-efficient Multi-subject Model for Predicting fMRI Activity
Connor Lane Gregory Kiar
This is the Algonauts 2023 submission report for team "BlobGPT". Our model
consists of a multi-subject linear encoding head attached to a pretrained trunk
model. The multi-subject head consists of three components: (1) a shared
multi-layer feature projection, (2) shared plus subject-specific low-dimension
linear transformations, and (3) a shared PCA fMRI embedding. In this report, we
explain these components in more detail and present some experimental results.
Our code is available at https://github.com/cmi-dair/algonauts23.