Export 17 results:
Filters: Author is Andrzej Banburski [Clear All Filters]
Neural Collapse in Deep Homogeneous Classifiers and the role of Weight Decay. IEEE International Conference on Acoustics, Speech and Signal Processing (2022).
Complexity Control by Gradient Descent in Deep Networks. Nature Communications 11, (2020).
Dreaming with ARC. Learning Meets Combinatorial Algorithms workshop at NeurIPS 2020 (2020).
An Overview of Some Issues in the Theory of Deep Networks. IEEJ Transactions on Electrical and Electronic Engineering 15, 1560 - 1571 (2020).
Theoretical issues in deep networks. Proceedings of the National Academy of Sciences 201907369 (2020). doi:10.1073/pnas.1907369117
Dynamics & Generalization in Deep Networks -Minimizing the Norm. NAS Sackler Colloquium on Science of Deep Learning (2019).
Theoretical Issues in Deep Networks. (2019).
Theories of Deep Learning: Approximation, Optimization and Generalization . TECHCON 2019 (2019).