Noise sensitivity and stability of deep neural networks for binary classification-Reference-Cited by-同舟云学术

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Noise sensitivity and stability of deep neural networks for binary classification

Published:2023-11 Issue: Volume:165 Page:130-167
ISSN:0304-4149
Container-title:Stochastic Processes and their Applications
language:en
Short-container-title:Stochastic Processes and their Applications

Author:

Jonasson Johan,Steif Jeffrey E.,Zetterqvist Olof^ORCID

Funder

Vetenskapsrådet

Knut och Alice Wallenbergs Stiftelse

Publisher

Elsevier BV

Subject

Applied Mathematics,Modeling and Simulation,Statistics and Probability

Reference14 articles.

1. Partially observed Boolean sequences and noise sensitivity;Ahlberg;Combin. Probab. Comput.,2014

2. Quenched voronoi percolation;Ahlberg;Adv. Math.,2016

3. On the rate of convergence in quenched voronoi percolation;Ahlberg;Electron. J. Probab.,2021

4. Noise sensitivity of boolean functions and applications to percolation;Benjamini;Publ. Math. Inst. Hautes Études Sci.,1999

5. Approximation by superpositions of a sigmoidal function;Cybenko;Math. Control Signals Systems,1989

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