Signal-to-Noise Ratio and Sample Size Govern Representational Alignment in Neural Networks

Neural networks are known to develop latent representations that are $aligned$, namely structurally similar across networks trained with different architectures, training protocols, or training datasets. We study this phenomenon in a controlled setting, where we train an ensemble of networks on regr...