Software Verification and Formal Methods for ML-Enabled Autonomous Systems
portes grátis
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
Isac, Omri; Nenzi, Laura; Ivanov, Radoslav; Narodytska, Nina; Katz, Guy
Springer International Publishing AG
12/2022
205
Mole
Inglês
9783031212215
15 a 20 dias
338
Descrição não disponível.
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
architecting;Autonomous Systems;computer networks;Control Theory;embedded systems;Explainable AI;Hybrid Systems;Interactive Theorem Proofs;Logic and Verification;machine learning;network protocols;Neural Network Verification;neural networks;Numerical Methods;Reachability Analysis;Satisfiability Modulo Theory;signal processing;software engineering;Statistical Verification
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
architecting;Autonomous Systems;computer networks;Control Theory;embedded systems;Explainable AI;Hybrid Systems;Interactive Theorem Proofs;Logic and Verification;machine learning;network protocols;Neural Network Verification;neural networks;Numerical Methods;Reachability Analysis;Satisfiability Modulo Theory;signal processing;software engineering;Statistical Verification
