On the robustness of neural networks

There is a new project we are beginning to look into which analyzes today’s neural networks in terms of stability and plasticity.
More explicitly, we evaluate how well these networks can cope with changes to their weights and how well they can adapt to new information. Some preliminary results suggest that if weights in lower layers are perturbed, this has a more severe effect on performance than if higher layers are perturbed. This has a nice correlation to neuroscience where it is assumed that our hierarchically lower cortical layers in the visual cortex remain rather fixed over the years.

Update: we just uploaded a version to arXiv (https://arxiv.org/abs/1703.08245) which is currently under review at ICML.