Activations of individual neurons are hardly relevant, quoting Szegedy et al. from [1]
we find that there is no distinction between individual high level units and
random linear combinations of high level units, according to various methods of
unit analysis. It suggests that it is the space, rather than the individual units, that
contains the semantic information in the high layers of neural networks.
we find that there is no distinction between individual high level units and random linear combinations of high level units, according to various methods of unit analysis. It suggests that it is the space, rather than the individual units, that contains the semantic information in the high layers of neural networks.
[1] Intriguing properties of neural networks