Artificial neural networks still lag behind brains in their ability to generalize beyond their training conditions. In this review, Sinz et al. discuss several ideas for how neuroscience can guide the search for better inductive biases by providing useful constraints on representations and network architecture.
from journals https://ift.tt/2l7ZXa7
from journals https://ift.tt/2l7ZXa7
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