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Robustness Certificates for Implicit Neural Networks: A Mixed Monotone
  Contractive Approach

Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach

10 December 2021
Saber Jafarpour
Matthew Abate
A. Davydov
Francesco Bullo
Samuel Coogan
    AAML
ArXiv (abs)PDFHTML

Papers citing "Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach"

5 / 5 papers shown
Title
Certified Robustness for Deep Equilibrium Models via Serialized Random
  Smoothing
Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing
Weizhi Gao
Zhichao Hou
Han Xu
Xiaorui Liu
AAML
70
0
0
01 Nov 2024
Improving Adversarial Robustness of DEQs with Explicit Regulations Along
  the Neural Dynamics
Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics
Zonghan Yang
Peng Li
Tianyu Pang
Yang Liu
AAML
73
3
0
02 Jun 2023
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models
Zonghan Yang
Tianyu Pang
Yang Liu
AAML
67
14
0
02 Jun 2023
Robust Training and Verification of Implicit Neural Networks: A
  Non-Euclidean Contractive Approach
Robust Training and Verification of Implicit Neural Networks: A Non-Euclidean Contractive Approach
Saber Jafarpour
A. Davydov
Matthew Abate
Francesco Bullo
Samuel Coogan
62
1
0
08 Aug 2022
Comparative Analysis of Interval Reachability for Robust Implicit and
  Feedforward Neural Networks
Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks
A. Davydov
Saber Jafarpour
Matthew Abate
Francesco Bullo
Samuel Coogan
34
3
0
01 Apr 2022
1