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Numerical Analysis

349 papers

Papers per year

2
19
32
12
'10
'15
'20
'25

Papers

SVD-NO: Learning PDE Solution Operators with SVD Integral Kernels AAAI 2026
Quantum Algorithms for Spectral Sums AAAI 2026
Adaptive Wavelet-Positional Encoding for High-Frequency Information Learning in Implicit Neural Representation AAAI 2025
Efficient Training of Neural Fractional-Order Differential Equation via Adjoint Backpropagation AAAI 2025
An Enhanced Levenberg--Marquardt Method via Gram Reduction AAAI 2025
Non-Convex Tensor Recovery from Local Measurements AAAI 2025
Preconditioners for the Stochastic Training of Neural Fields CVPR 2025
Matrix-Free Shared Intrinsics Bundle Adjustment CVPR 2025
Linear Trading Position with Sparse Spectrum IJCAI 2025
FreqMoE: Dynamic Frequency Enhancement for Neural PDE Solvers IJCAI 2025
A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation JMLR 2025
On the Approximation of Kernel functions JMLR 2025
Operator Learning for Hyperbolic PDEs JMLR 2025
Precise Integral in NeRFs: Overcoming the Approximation Errors of Numerical Quadrature WACV 2025
Towards Scalable and Stable Parallelization of Nonlinear RNNs NIPS 2024
AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields NIPS 2024
Generalized Tensor Decomposition for Understanding Multi-Output Regression under Combinatorial Shifts NIPS 2024
Gradients of Functions of Large Matrices NIPS 2024
Alias-Free Mamba Neural Operator NIPS 2024
Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees NIPS 2024
Efficient Leverage Score Sampling for Tensor Train Decomposition NIPS 2024
Distributed Least Squares in Small Space via Sketching and Bias Reduction NIPS 2024
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs NIPS 2024
RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks NIPS 2024
Linear Time Approximation Algorithm for Column Subset Selection with Local Search NIPS 2024