Cover Image

Learning to Integrate

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ernst, Oliver G., Gottschalk, Hanno, Kowalewitz, Toni, Krüger, Patrick
Format:	Preprint
Published:	2025
Subjects:	Numerical Analysis Probability 65C30 (Primary) 65D40, 68T07 (Secondary)
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Consistency of Learned Sparse Grid Quadrature Rules using NeuralODEs
by: Gottschalk, Hanno, et al.
Published: (2025)

Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks
by: Adcock, Ben, et al.
Published: (2022)

Deep Learning Based on Randomized Quasi-Monte Carlo Method for Solving Linear Kolmogorov Partial Differential Equation
by: Xiao, Jichang, et al.
Published: (2023)

Performance of Neural and Polynomial Operator Surrogates
by: Westermann, Josephine, et al.
Published: (2026)

Residual Multi-Fidelity Neural Network Computing
by: Davis, Owen, et al.
Published: (2023)

Fourier Residual Networks Achieve Spectral Accuracy for Discontinuous Functions
by: Davis, Owen, et al.
Published: (2026)

Numerical PDE solvers outperform neural PDE solvers
by: Chatain, Patrick, et al.
Published: (2025)

Neural Shape Operator Surrogates -- Expression Rate Bounds
by: Harbrecht, Helmut, et al.
Published: (2026)

On the algorithmic construction of deep ReLU networks
by: Huybrechs, Daan
Published: (2025)

Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for space-time solutions of semilinear partial differential equations
by: Ackermann, Julia, et al.
Published: (2024)

Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for Kolmogorov partial differential equations with Lipschitz nonlinearities in the $L^p$-sense
by: Ackermann, Julia, et al.
Published: (2023)

Using the Immersed Penalized Boundary Method with Splines to Solve PDE's on Curved Domains in 3D
by: Greene, Aussie, et al.
Published: (2025)

Rigorous High-Order Hausdorff Dimension Estimation of Limit Sets of Continued Fraction Iterated Function Systems via B-Splines
by: Brown, Jacob
Published: (2026)

Learning Contractive Integral Operators with Fredholm Integral Neural Operators
by: Georgiou, Kyriakos C., et al.
Published: (2026)

A C^s-smooth mixed degree and regularity isogeometric spline space over planar multi-patch domains
by: Kapl, Mario, et al.
Published: (2024)

The local coupling of noise technique and its application to lower error bounds for strong approximation of SDEs with irregular coefficients
by: Ellinger, Simon
Published: (2025)

On optimal error rates for strong approximation of SDEs with a Hölder continuous drift coefficient
by: Ellinger, Simon, et al.
Published: (2025)

On optimal error rates for strong approximation of SDEs with a drift coefficient of fractional Sobolev regularity
by: Ellinger, Simon, et al.
Published: (2024)

On the complexity of strong approximation of stochastic differential equations with a non-Lipschitz drift coefficient
by: Müller-Gronbach, T., et al.
Published: (2024)

Algebraic Reconstruction of Piecewise-Smooth Functions of Two Variables from Fourier Data
by: Levinov, Michael, et al.
Published: (2025)

Parametric Numerical Integration with (Differential) Machine Learning
by: Leitao, Álvaro, et al.
Published: (2025)

Reduced Order Modeling of Partial Differential Equations on Parameter-Dependent Domains Using Deep Neural Networks
by: Bukač, Martina, et al.
Published: (2024)

Regularity and tailored regularization of Deep Neural Networks, with application to parametric PDEs in uncertainty quantification
by: Keller, Alexander, et al.
Published: (2025)

Quadrature-Free Polytopic Discontinuous Galerkin Methods for Transport Problems
by: Radley, Thomas J., et al.
Published: (2023)

A Theory-guided Weighted $L^2$ Loss for solving the BGK model via Physics-informed neural networks
by: Ko, Gyounghun, et al.
Published: (2026)

Deep Neural Networks and Finite Elements of Any Order on Arbitrary Dimensions
by: He, Juncai, et al.
Published: (2023)

Error bounds for Physics Informed Neural Networks in Nonlinear Schrödinger equations placed on unbounded domains
by: Alejo, Miguel Á., et al.
Published: (2024)

Pressure-robustness for the axisymmetric Stokes problem by velocity reconstruction
by: Lederer, Philip L., et al.
Published: (2026)

Theoretical guarantees for stochastic gradient sampling methods via Gaussian convolution inequalities
by: Paulin, Daniel, et al.
Published: (2026)

Trustworthy AI in numerics: On verification algorithms for neural network-based PDE solvers
by: Haugen, Emil, et al.
Published: (2025)

Deep Micro Solvers for Rough-Wall Stokes Flow in a Heterogeneous Multiscale Method
by: Ström, Emanuel, et al.
Published: (2025)

Accuracy and stability of Artificial Neural Networks for HP-Splines frequency parameter selection
by: Bruni, Vittoria, et al.
Published: (2026)

A multilevel Monte Carlo algorithm for SDEs driven by countably dimensional Wiener process and Poisson random measure
by: Sobieraj, Michał
Published: (2023)

A neuron-wise subspace correction method for the finite neuron method
by: Park, Jongho, et al.
Published: (2022)

Error analysis for learning fractional stochastic differential equations with applications in neural approximations
by: Dehshiri, Mahdi, et al.
Published: (2026)

Möbius-Transformed Trapezoidal Rule
by: Suzuki, Yuya, et al.
Published: (2024)

Convergence analysis and adaptive computation of a Banach-space mixed finite element method for generalized bioconvective flows
by: Colmenares, Eligio, et al.
Published: (2026)

Certified and accurate computation of function space norms of deep neural networks
by: Gründler, Johannes, et al.
Published: (2026)

The sharpness condition for constructing a finite element from a superspline
by: Hu, Jun, et al.
Published: (2024)

STM Image Analysis using Autoencoders
by: Binev, Peter, et al.
Published: (2025)