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Reachability Is NP-Complete Even for the Simplest Neural Networks

Reachability Is NP-Complete Even for the Simplest Neural Networks

30 August 2021
Marco Salzer
M. Lange
ArXivPDFHTML

Papers citing "Reachability Is NP-Complete Even for the Simplest Neural Networks"

15 / 15 papers shown
Title
Revisiting Differential Verification: Equivalence Verification with Confidence
Revisiting Differential Verification: Equivalence Verification with Confidence
Samuel Teuber
Philipp Kern
Marvin Janzen
Bernhard Beckert
38
0
0
26 Oct 2024
Local vs. Global Interpretability: A Computational Complexity
  Perspective
Local vs. Global Interpretability: A Computational Complexity Perspective
Shahaf Bassan
Guy Amir
Guy Katz
35
6
0
05 Jun 2024
Certifying Robustness of Graph Convolutional Networks for Node
  Perturbation with Polyhedra Abstract Interpretation
Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation
Boqi Chen
Kristóf Marussy
Oszkár Semeráth
Gunter Mussbacher
Dániel Varró
AAML
24
0
0
14 May 2024
Robustness Verifcation in Neural Networks
Robustness Verifcation in Neural Networks
Adrian Wurm
21
0
0
20 Mar 2024
Provably Safe Neural Network Controllers via Differential Dynamic Logic
Provably Safe Neural Network Controllers via Differential Dynamic Logic
Samuel Teuber
Stefan Mitsch
André Platzer
AAML
27
8
0
16 Feb 2024
STR-Cert: Robustness Certification for Deep Text Recognition on Deep
  Learning Pipelines and Vision Transformers
STR-Cert: Robustness Certification for Deep Text Recognition on Deep Learning Pipelines and Vision Transformers
Daqian Shao
Lukas Fesser
Marta Z. Kwiatkowska
26
0
0
28 Nov 2023
OccRob: Efficient SMT-Based Occlusion Robustness Verification of Deep
  Neural Networks
OccRob: Efficient SMT-Based Occlusion Robustness Verification of Deep Neural Networks
Xingwu Guo
Ziwei Zhou
Yueling Zhang
Guy Katz
M. Zhang
AAML
34
5
0
27 Jan 2023
Verifying And Interpreting Neural Networks using Finite Automata
Verifying And Interpreting Neural Networks using Finite Automata
Marco Salzer
Eric Alsmann
Florian Bruse
M. Lange
AAML
25
3
0
02 Nov 2022
Learning Provably Stabilizing Neural Controllers for Discrete-Time
  Stochastic Systems
Learning Provably Stabilizing Neural Controllers for Discrete-Time Stochastic Systems
Matin Ansaripour
K. Chatterjee
T. Henzinger
Mathias Lechner
Dorde Zikelic
27
4
0
11 Oct 2022
Provably Tightest Linear Approximation for Robustness Verification of
  Sigmoid-like Neural Networks
Provably Tightest Linear Approximation for Robustness Verification of Sigmoid-like Neural Networks
Zhaodi Zhang
Yiting Wu
Siwen Liu
Jing Liu
Min Zhang
AAML
26
11
0
21 Aug 2022
Fundamental Limits in Formal Verification of Message-Passing Neural
  Networks
Fundamental Limits in Formal Verification of Message-Passing Neural Networks
Marco Salzer
M. Lange
GNN
11
9
0
10 Jun 2022
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot
  Learning
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning
Mathias Lechner
Alexander Amini
Daniela Rus
T. Henzinger
AAML
26
9
0
15 Apr 2022
Reachability In Simple Neural Networks
Reachability In Simple Neural Networks
Marco Salzer
M. Lange
11
1
0
15 Mar 2022
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
292
10,618
0
19 Feb 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
231
1,837
0
03 Feb 2017
1