{"total":18,"rows":[{"id":"2207.00556","title":"Learning to correct spectral methods for simulating turbulent flows","created":"2022-07-01","cited_by_count":49,"area":null},{"id":"2402.04467","title":"DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems","created":"2024-02-06","cited_by_count":30,"area":null},{"id":"2302.08105","title":"A Neural PDE Solver with Temporal Stencil Modeling","created":"2023-02-16","cited_by_count":22,"area":null},{"id":"2102.12071","title":"Learning optimal multigrid smoothers via neural networks","created":"2021-02-24","cited_by_count":17,"area":null},{"id":"2301.10391","title":"Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems","created":"2023-01-25","cited_by_count":14,"area":null},{"id":"2306.01174","title":"Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations","created":"2023-06-01","cited_by_count":13,"area":null},{"id":"2405.05192","title":"Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs","created":"2024-05-08","cited_by_count":12,"area":null},{"id":"2211.12386","title":"A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms","created":"2022-11-22","cited_by_count":8,"area":null},{"id":"2303.16110","title":"Invariant preservation in machine learned PDE solvers via error correction","created":"2023-03-28","cited_by_count":7,"area":null},{"id":"2304.10832","title":"A Deep Learning algorithm to accelerate Algebraic Multigrid methods in Finite Element solvers of 3D elliptic PDEs","created":"2023-04-21","cited_by_count":6,"area":null},{"id":"2302.10184","title":"AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios","created":"2023-02-05","cited_by_count":4,"area":null},{"id":"2112.11360","title":"Multigoal-oriented dual-weighted-residual error estimation using deep neural networks","created":"2021-12-21","cited_by_count":2,"area":null},{"id":"2207.11255","title":"Learning Relaxation for Multigrid","created":"2022-07-25","cited_by_count":2,"area":null},{"id":"2101.06182","title":"STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations","created":"2021-01-15","cited_by_count":1,"area":null},{"id":"2302.03286","title":"Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equations","created":"2023-02-07","cited_by_count":1,"area":null},{"id":"2509.02617","title":"Gaussian process surrogate with physical law-corrected prior for multi-coupled PDEs defined on irregular geometry","created":"2025-09-01","cited_by_count":1,"area":null},{"id":"2409.09217","title":"Rational-WENO: A lightweight, physically-consistent three-point weighted essentially non-oscillatory scheme","created":"2024-09-13","cited_by_count":0,"area":null},{"id":"2503.09625","title":"Learning second-order TVD flux limiters using differentiable solvers","created":"2025-03-11","cited_by_count":0,"area":null}],"next_cursor":null}