[Article] What can 5.17 billion regression fits tell us about artificial models of the human visual system?

Summary: They performed a large-scale benchmarking analysis of 85 modern deep neural network models (e.g. CLIP, BarlowTwins,Mask-RCNN). They found that architectural differences have very little consequence in emergent fits to brain data. Next, differences in task have clear effects–with categorization and self-supervised models showing relatively stronger brain predictivity.

Conwell, C., Prince, J. S., Alvarez, G. A., & Konkle, T. (2021, October). What can 5.17 billion regression fits tell us about artificial models of the human visual system?. In SVRHM 2021 Workshop@ NeurIPS.