differential operator

STDE++: Polynomial-Time Amortization for Linear Differential Operators JMLR 2026 Accelerating PDE Data Generation via Differential Operator Action in Solution Space ICML 2024 An operator preconditioning perspective on training in physics-informed machine learning ICLR 2024 Challenges in Training PINNs: A Loss Landscape Perspective ICML 2024 Neural Operators with Localized Integral and Differential Kernels ICML 2024 PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling ICML 2024 Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators NeurIPS 2024 The Galerkin method beats Graph-Based Approaches for Spectral Algorithms AISTATS 2024 Neural Fields with Hard Constraints of Arbitrary Differential Order NeurIPS 2023 Radial Basis Approximation of Tensor Fields on Manifolds: From Operator Estimation to Manifold Learning JMLR 2023 Universal Physics-Informed Neural Networks: Symbolic Differential Operator Discovery with Sparse Data ICML 2023 When Locally Linear Embedding Hits Boundary JMLR 2023 Signal Processing for Implicit Neural Representations NeurIPS 2022 DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling NeurIPS 2020 Neural Networks with Cheap Differential Operators NeurIPS 2019 Spherical CNNs on Unstructured Grids ICLR 2019 PDE-Net: Learning PDEs from Data ICML 2018 Beyond Gaussian Pyramid: Multi-Skip Feature Stacking for Action Recognition CVPR 2015