Neural operators approximate strongly continuous convex monotone semigroups
math.NA, cs.LG, cs.NA, math.AP, math.PR, stat.ML
Submitted: 2026-09-02
Updated: 2026-09-02
Comments: 38 pages, 6 figures
Code: https://github.com/sgarale/chernoff_
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Discrete approximation of risk-based prices under volatility uncertainty
- Deep neural network approximation for high-dimensional parabolic Hamilton-Jacobi-Bellman equations
- Deep Learning Approximation for Stochastic Control Problems
- Kernel Learning of PDE Solution Operators
- An Approximation Theory for Metric Space-Valued Functions With A View Towards Deep Learning
- Neural Operators Which Certifiably Simultaneously Solve Infinitely Many Convex Programs using Logarithmic Rank and Linear Complexity
- Fourier Neural Operator for Parametric Partial Differential Equations
- Mathematical theory of deep learning
- Weighted universal approximation of differentiable maps on infinite-dimensional manifolds
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