Understanding the effect of sparsity on neural networks robustness

Lukas Timpl, Rahim Entezari, Hanie Sedghi, Behnam Neyshabur, Olga Saukh

Institut für Technische Informatik (4480)

Publikation: Arbeitspapier › Preprint

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2022
Studying the impact of magnitude pruning on contrastive learning methods
Corti, F., Entezari, R., Bacciu, D., Hooker, S. & Saukh, O., 1 Juli 2022, arXiv, S. 1-10, 10 S.
Publikation: Arbeitspapier › Preprint