Software Verification and Formal Methods for ML-Enabled Autonomous Systems: 5th International Workshop, FoMLAS 2022, and 15th International Workshop, NSV 2022, Haifa, Israel, July 31 - August 1, and August 11, 2022, Proceedings

Author:   Omri Isac ,  Radoslav Ivanov ,  Guy Katz ,  Nina Narodytska
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2022
Volume:   13466
ISBN:  

9783031212215


Pages:   205
Publication Date:   16 December 2022
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Software Verification and Formal Methods for ML-Enabled Autonomous Systems: 5th International Workshop, FoMLAS 2022, and 15th International Workshop, NSV 2022, Haifa, Israel, July 31 - August 1, and August 11, 2022, Proceedings


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Author:   Omri Isac ,  Radoslav Ivanov ,  Guy Katz ,  Nina Narodytska
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2022
Volume:   13466
Weight:   0.338kg
ISBN:  

9783031212215


ISBN 10:   3031212215
Pages:   205
Publication Date:   16 December 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

FoMLAS 2022.- VPN: Verification of Poisoning in Neural Networks.- A Cascade of Checkers for Run-time Certification of Local Robustness.- CEG4N: Counter-Example Guided Neural Network Quantization Refinement .- Minimal Multi-Layer Modifications of Deep Neural Networks.- Differentiable Logics for Neural Network Training and Verification.- Neural Networks in Imandra: Matrix Representation as a Verification Choice.- Self-Correcting Neural Networks For Safe Classification.- Self-Correcting Neural Networks For Safe Classification.- NSV 2022.- Verified Numerical Methods for Ordinary Differential Equations.- Neural Network Precision Tuning Using Stochastic Arithmetic.- MLTL Multi-type (MLTLM): A Logic for Reasoning about Signals of Different Types.

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