A survey of dual-use LLM applications in cybersecurity, synthesizing defensive tools, attack vectors, governance frameworks, and the projected growth of AI-assisted malware through 2025.
Parameter identification in PDEs by the solution of monotone inclusion problems
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abstract
In this paper we consider the solution of monotone inverse problems using the particular example of a parameter identification problem for a semilinear parabolic PDE. For the regularized solution of this problem, we introduce a total variation based regularization method requiring the solution of a monotone inclusion problem. We show well-posedness in the sense of inverse problems of the resulting regularization scheme. In addition, we introduce and analyze a numerical algorithm for the solution of this inclusion problem using a nested inertial primal dual method. We demonstrate by means of numerical examples the convergence of both the numerical algorithm and the regularization method.
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cs.CR 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
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