{"total":29,"rows":[{"id":"2405.19166","title":"Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity","created":"2024-05-29","cited_by_count":34,"area":null},{"id":"2401.08886","title":"RiemannONets: Interpretable Neural Operators for Riemann Problems","created":"2024-01-16","cited_by_count":28,"area":null},{"id":"2312.05410","title":"Rethinking materials simulations: Blending direct numerical simulations with neural operators","created":"2023-12-08","cited_by_count":25,"area":null},{"id":"2410.00171","title":"Basis-to-Basis Operator Learning Using Function Encoders","created":"2024-09-30","cited_by_count":17,"area":null},{"id":"2410.00357","title":"Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study","created":"2024-10-01","cited_by_count":14,"area":null},{"id":"2501.00016","title":"Predicting Crack Nucleation and Propagation in Brittle Materials Using Deep Operator Networks with Diverse Trunk Architectures","created":"2024-12-15","cited_by_count":12,"area":null},{"id":"2504.11383","title":"Time Marching Neural Operator FE Coupling: AI Accelerated Physics Modeling","created":"2025-04-15","cited_by_count":8,"area":null},{"id":"2409.13280","title":"Efficient Training of Deep Neural Operator Networks via Randomized Sampling","created":"2024-09-20","cited_by_count":6,"area":null},{"id":"2509.14198","title":"A Variational Framework for Residual-Based Adaptivity in Neural PDE Solvers and Operator Learning","created":"2025-09-17","cited_by_count":6,"area":null},{"id":"2601.11428","title":"Diagnosing Failure Modes of Neural Operators Across Diverse PDE Families","created":"2026-01-16","cited_by_count":6,"area":null},{"id":"2406.10920","title":"Hamilton-Jacobi Based Policy-Iteration via Deep Operator Learning","created":"2024-06-16","cited_by_count":5,"area":null},{"id":"2508.03965","title":"BubbleOKAN: A Physics-Informed Interpretable Neural Operator for High-Frequency Bubble Dynamics","created":"2025-08-05","cited_by_count":5,"area":null},{"id":"2602.16530","title":"FEKAN: Feature-Enriched Kolmogorov-Arnold Networks","created":"2026-02-18","cited_by_count":5,"area":null},{"id":"2507.10401","title":"Stochastic Operator Network: A Stochastic Maximum Principle Based Approach to Operator Learning","created":"2025-07-10","cited_by_count":4,"area":null},{"id":"2512.13746","title":"Probabilistic Predictions of Process-Induced Deformation in Carbon/Epoxy Composites Using a Deep Operator Network","created":"2025-12-15","cited_by_count":3,"area":null},{"id":"2507.03660","title":"Single vs. Multiple Branches in DeepONet and S-DeepONet: Network Architecture Follows Coupling in Multiphysics Systems","created":"2025-07-04","cited_by_count":2,"area":null},{"id":"2510.12999","title":"AMORE: Adaptive Multi-Output Operator Network for Stiff Chemical Kinetics","created":"2025-10-15","cited_by_count":2,"area":null},{"id":"2503.19717","title":"Invertible Koopman neural operator for data-driven modeling of partial differential equations","created":"2025-03-25","cited_by_count":1,"area":null},{"id":"2504.10720","title":"Leveraging Deep Operator Networks (DeepONet) for Acoustic Full Waveform Inversion (FWI)","created":"2025-04-14","cited_by_count":1,"area":null},{"id":"2509.11966","title":"Deep operator network for surrogate modeling of poroelasticity with random permeability fields","created":"2025-09-15","cited_by_count":1,"area":null},{"id":"2602.12706","title":"Physics-Informed Laplace Neural Operator for Solving Partial Differential Equations","created":"2026-02-13","cited_by_count":1,"area":null},{"id":"2606.21828","title":"Spectrally Safe Neural Operator Warm-Starts for Large-Scale Newton Solvers","created":"2026-06-20","cited_by_count":1,"area":null},{"id":"2407.17182","title":"A DeepONet for inverting the Neumann-to-Dirichlet Operator in Electrical Impedance Tomography: An approximation theoretic perspective and numerical results","created":"2024-07-24","cited_by_count":0,"area":null},{"id":"2410.20951","title":"Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics?","created":"2024-10-28","cited_by_count":0,"area":null},{"id":"2506.01976","title":"Crack Path Prediction with Operator Learning using Discrete Particle System data Generation","created":"2025-05-15","cited_by_count":0,"area":null},{"id":"2602.21910","title":"The Error of Deep Operator Networks Is the Sum of Its Parts: Branch-Trunk and Mode Error Decompositions","created":"2026-02-25","cited_by_count":0,"area":null},{"id":"2606.29436","title":"Fourier Neural Operators with Least-Squares Readout Refit for Learning Random Obstacle-to-Solution Maps","created":"2026-06-28","cited_by_count":0,"area":null},{"id":"2608.09071","title":"Two-Step MV-DeepONet: Probabilistic Operator Learning for Uncertainty Propagation Driven by Random Input Fields","created":"2026-08-10","cited_by_count":0,"area":null},{"id":"2608.24426","title":"Sequential operator learning under dependent data","created":"2026-08-25","cited_by_count":0,"area":null}],"next_cursor":null}