Search Results for author:
Found 3 papers, 0 papers with code
Lateral predictive coding revisited: Internal model, symmetry breaking, and response time
Predictive coding is a promising theoretical framework in neuroscience for understanding information transmission and perception.
Relationship between manifold smoothness and adversarial vulnerability in deep learning with local errors
Here, we establish a fundamental relationship between geometry of hidden representations (manifold perspective) and the generalization capability of the deep networks.
Weakly-correlated synapses promote dimension reduction in deep neural networks
Here we propose a simplified model of dimension reduction, taking into account pairwise correlations among synapses, to reveal the mechanism underlying how the synaptic correlations affect dimension reduction.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
