A domain-theoretic framework for robustness analysis of neural networks

DOI10.1017/s0960129523000142arXiv2203.00295OpenAlexW4377822310MaRDI QIDQ6149907

Amin Farjudian, Yiran Li, Can Zhou, Unnamed Author

Publication date: 5 March 2024

Published in: Mathematical Structures in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2203.00295

zbMATH Keywords

robustnessneural networkLipschitz constantdomain theoryClarke-gradient

Mathematics Subject Classification ID

Computer science (68-XX)

Cites Work

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• Strictness analysis for higher-order functions
• Effectively given domains
• A domain-theoretic approach to computability on the real line
• Concrete models of computation for topological algebras
• Properly injective spaces and function spaces
• The way-below relation of function spaces over semantic domains
• Safe \& robust reachability analysis of hybrid systems
• Integration in Real PCF
• Dynamical systems, measures, and fractals via domain theory
• Real number computability and domain theory
• Domain theoretic second-order Euler's method for solving initial value problems
• Exploiting verified neural networks via floating point numerical error
• Abstract neural networks
• Motivations for an arbitrary precision interval arithmetic and the MPFI library
• SHRAD: A language for sequential real number computation
• Denotational semantics of hybrid automata
• Clarke's generalized gradient and Edalat's L-derivative
• Abstract Interpretation, Logical Relations, and Kan Extensions
• A Domain-Theoretic Account of Picard's Theorem
• Introduction to Interval Analysis
• Domains for Computation in Mathematics, Physics and Exact Real Arithmetic
• Domain theory and differential calculus (functions of one variable)
• Continuous Lattices and Domains
• A Language for Differentiable Functions
• Non-Hausdorff Topology and Domain Theory
• Benign overfitting in linear regression
• System analysis and robustness