{"total":15,"rows":[{"id":"2406.18794","title":"Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective","created":"2024-06-26","cited_by_count":11,"area":null},{"id":"2508.14995","title":"Generative Neural Operators of Log-Complexity Can Simultaneously Solve Infinitely Many Convex Programs","created":"2025-08-20","cited_by_count":7,"area":null},{"id":"2410.02151","title":"Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations","created":"2024-10-03","cited_by_count":5,"area":null},{"id":"2411.09644","title":"Neural Operators Can Play Dynamic Stackelberg Games","created":"2024-11-14","cited_by_count":5,"area":null},{"id":"2502.15496","title":"Verification and Validation for Trustworthy Scientific Machine Learning","created":"2025-02-21","cited_by_count":4,"area":null},{"id":"2511.01125","title":"One model to solve them all: 2BSDE families via neural operators","created":"2025-11-03","cited_by_count":4,"area":null},{"id":"2405.20094","title":"Low-dimensional approximations of the conditional law of Volterra processes: a non-positive curvature approach","created":"2024-05-30","cited_by_count":3,"area":null},{"id":"2504.02321","title":"On shallow feedforward neural networks with inputs from a topological space","created":"2025-04-03","cited_by_count":2,"area":null},{"id":"2512.01015","title":"Upper Approximation Bounds for Neural Oscillators","created":"2025-11-30","cited_by_count":1,"area":null},{"id":"2602.11197","title":"Hybrid operator learning of wave scattering maps in high-contrast media","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2602.23381","title":"Universality of shallow and deep neural networks on non-Euclidean spaces","created":"2026-02-03","cited_by_count":0,"area":null},{"id":"2602.23528","title":"Neural Operators Can Discover Functional Clusters","created":"2026-02-26","cited_by_count":0,"area":null},{"id":"2605.08559","title":"Structure-Preserving Reconstruction of Convex Lipschitz Functionals on Hilbert Spaces from Finite Samples","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2605.12025","title":"Approximation Theory of Laplacian-Based Neural Operators for Reaction-Diffusion System","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2608.30070","title":"Selection, Representation, and Execution in Sparse Fourier Neural Operators","created":"2026-08-30","cited_by_count":0,"area":null}],"next_cursor":null}