partial differential equation

Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical Systems NeurIPS 2021 Differential Spectral Normalization (DSN) for PDE Discovery AAAI 2021 DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation AAAI 2021 Fourier Neural Operator for Parametric Partial Differential Equations ICLR 2021 Functional Space Analysis of Local GAN Convergence ICML 2021 GRAND: Graph Neural Diffusion ICML 2021 Learning continuous-time PDEs from sparse data with graph neural networks ICLR 2021 Learning Stochastic Behaviour from Aggregate Data ICML 2021 Linearly Constrained Gaussian Processes with Boundary Conditions AISTATS 2021 Low-Rank Registration Based Manifolds for Convection-Dominated PDEs AAAI 2021 LSH-SMILE: Locality Sensitive Hashing Accelerated Simulation and Learning NeurIPS 2021 Multi-Fidelity High-Order Gaussian Processes for Physical Simulation AISTATS 2021 Multiwavelet-based Operator Learning for Differential Equations NeurIPS 2021 NTopo: Mesh-free Topology Optimization using Implicit Neural Representations NeurIPS 2021 Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm NeurIPS 2021 On the Representation of Solutions to Elliptic PDEs in Barron Spaces NeurIPS 2021 On Universal Approximation and Error Bounds for Fourier Neural Operators JMLR 2021 Parametric Complexity Bounds for Approximating PDEs with Neural Networks NeurIPS 2021 PDE-Driven Spatiotemporal Disentanglement ICLR 2021 PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations NeurIPS 2021 Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling NeurIPS 2021 Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning IJCAI 2021 Probabilistic Numeric Convolutional Neural Networks ICLR 2021 Rethinking Neural Operations for Diverse Tasks NeurIPS 2021 SPDE-Net: Neural Network based prediction of stabilization parameter for SUPG technique ACML 2021