Reading - nguyenthanhvuh/class-verification GitHub Wiki
Papers to read
Verifier
- alpha-beta-CROWN: Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification by Wang et al., 2021
- MN-BaB (ERAN): Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound by Ferrari et al., 2022
- VeriNet: Efficient Neural Network Verification via Adaptive Refinement and Adversarial Search by Henriksen et al., 2020
- nnenum: Improved Geometric Path Enumeration for Verifying ReLU Neural Networks by Stanley et al., 2020
- Marabou: The Marabou Framework for Verification and Analysis of Deep Neural Networks by Katz et al., 2019
- Reluplex: Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks by Katz et al., 2017
- BaB (Oval): Branch and Bound for Piecewise Linear Neural Network Verification by Bunel et al., 2020
- ReluVal: Formal Security Analysis of Neural Networks using Symbolic Intervals by Wang et al., 2018
- Neurify: Efficient Formal Safety Analysis of Neural Networks by Wang et al., 2018
- Planet: Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks by Ehlers, 2017
- MIPVerify: Evaluating Robustness of Neural Networks with Mixed Integer Programming by Tjeng et al., 2019
- DeepPoly: An Abstract Domain for Certifying Neural Networks by Singh et al., 2019
- DeepZ: Fast and Effective Robustness Certification by Singh et al., 2018
Abstraction
Surveys/Books
- Trustworthy Artificial Intelligence: A Review by Kaur et al., 2022
- Algorithms for Verifying Deep Neural Networks by Liu et al., 2020
- Introduction to Neural Network Verification by Albarghouthi, 2019
- A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability by Huang et al., 2020
- Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
by Meng et al., 2022
- AAAI 2022 Tutorial on Neural Network Verification Part II: Algorithms for NN Verification (slides) by Zhang et al., 2022
- Neural Network Verification Tutorial by Zhang et al., 2022
- Automated Verification of Neural Networks: Advances, Challenges and Perspectives by
Francesco Leofante, et al, 2018
- Neural network verification: Where are we and where do we go from here?
by Aws Albarghouthi, 2021
Miscs
Class