Stable neural ODE with Lyapunov-stable equilibrium points for defending against adversarial attacks

Stable neural ODE with Lyapunov-stable equilibrium points for defending against adversarial attacks

Deep neural networks (DNNs) are well-known to be vulnerable to adversarial attacks, where malicious human-imperceptible perturbations are included in the input to the deep network to fool it into making a wrong classification. Recent studies have demonstrated that neural Ordinary Differential Equati...

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Bibliographic Details
Main Authors: Kang, Qiyu, Song, Yang, Ding, Qinxu, Tay, Wee Peng
Other Authors: School of Electrical and Electronic Engineering
Format: Conference Paper
Language:English
Published: 2023
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Deep Neural Networks
Adversarial Attacks
Online Access:https://hdl.handle.net/10356/166692
https://nips.cc/Conferences/2021
https://proceedings.neurips.cc/

Internet

https://hdl.handle.net/10356/166692
https://nips.cc/Conferences/2021
https://proceedings.neurips.cc/

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