Non-asymptotic stability and consistency guarantees for physics-informed neural networks via coercive operator analysis

Communications in Nonlinear Science and Numerical Simulation 2026 Open access

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Authors: Ronald Katende
DOI: 10.1016/j.cnsns.2026.109909
Cited by: 0
References: 9

Fields of Study & Subjects

Model Reduction and Neural Networks Quantum many-body systems Advanced Graph Neural Networks

Publication details

Journal / source
Communications in Nonlinear Science and Numerical Simulation
Volume
159
Pages
109909–109909
Publication date
14 March 2026
Language
EN