numerical analysis

Operator Learning for Hyperbolic PDEs JMLR 2025 Alias-Free Mamba Neural Operator NeurIPS 2024 Iterative Methods via Locally Evolving Set Process NeurIPS 2024 Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees NeurIPS 2024 PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs NeurIPS 2024 RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks NeurIPS 2024 Stable Implementation of Probabilistic ODE Solvers JMLR 2024 The Galerkin method beats Graph-Based Approaches for Spectral Algorithms AISTATS 2024 Constructive TT-representation of the tensors given as index interaction functions with applications ICLR 2023 Near Optimal Reconstruction of Spherical Harmonic Expansions NeurIPS 2023 Online PCA in Converging Self-consistent Field Equations NeurIPS 2023 Approximate Euclidean lengths and distances beyond Johnson-Lindenstrauss NeurIPS 2022 Black Box Probabilistic Numerics NeurIPS 2021 Comparison of the Finite Element Method, the Multimodal Method and the Transmission-Line Model for the Computation of Vocal Tract Transfer Functions Interspeech 2021 Higher-order Derivatives of Weighted Finite-state Machines ACL 2021 Linear-Time Probabilistic Solution of Boundary Value Problems NeurIPS 2021 Square Root Bundle Adjustment for Large-Scale Reconstruction CVPR 2021 Shadowing Properties of Optimization Algorithms NeurIPS 2019 Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations ICML 2018 Implicit Probabilistic Integrators for ODEs NeurIPS 2018 Integration Methods and Optimization Algorithms NeurIPS 2017 Sublinear Time Orthogonal Tensor Decomposition NeurIPS 2016 A Wavefront Marching Method for Solving the Eikonal Equation on Cartesian Grids ICCV 2015 large scale canonical correlation analysis with iterative least squares NeurIPS 2014