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Numerical Integration

Numerical integration is the task to calculate the numerical value of a definite integral or the numerical solution of differential equations.

Papers

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Showing 1–50 of 242 papers

TitleStatusHype
Gaussian Processes and Reproducing Kernels: Connections and Equivalences—0
Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models—0
How Far Are We from Optimal Reasoning Efficiency?Code0
ODE-GS: Latent ODEs for Dynamic Scene Extrapolation with 3D Gaussian Splatting—0
Operator-Splitting Methods for Neuromorphic Circuit Simulation—0
Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space—0
Continuous-time iterative linear-quadratic regulator—0
Discretization of Linear Systems using the Matrix Exponential—0
A Dictionary of Closed-Form Kernel Mean EmbeddingsCode0
On the Eigenvalue Tracking of Large-Scale Systems—0
Asian Basket Spread Options: A New Approximation Based on Stochastic Taylor Expansions—0
Riemannian Patch Assignment Gradient Flows—0
Neural network-enhanced integrators for simulating ordinary differential equations—0
Force-Free Molecular Dynamics Through Autoregressive Equivariant NetworksCode2
Computing Modes of Instability of Parameterized Nonlinear Systems for Vulnerability Assessment—0
PI-Controlled Variable Time-Step Power System Simulation Using an Adaptive Order Differential Transformation Method—0
Denoising Hamiltonian Network for Physical Reasoning—0
Underdamped Diffusion Bridges with Applications to SamplingCode1
Provable Quantum Algorithm Advantage for Gaussian Process QuadratureCode0
EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems—0
FNIN: A Fourier Neural Operator-based Numerical Integration Network for Surface-form-gradientsCode1
Lilan: A linear latent network approach for real-time solutions of stiff, nonlinear, ordinary differential equations—0
Median of Means Sampling for the Keister Function—0
Time-Reversible Bridges of Data with Machine Learning—0
Predicting Change, Not States: An Alternate Framework for Neural PDE SurrogatesCode0
Graph Spring Neural ODEs for Link Sign Prediction—0
Importance Sampling With Stochastic Particle Flow and Diffusion Optimization—0
Data-Augmented Numerical Integration in State Prediction: Rule Selection—0
Modular addition without black-boxes: Compressing explanations of MLPs that compute numerical integration—0
Beyond Monte Carlo: Harnessing Diffusion Models to Simulate Financial Market Dynamics—0
Adaptive Process-Guided Learning: An Application in Predicting Lake DO ConcentrationsCode0
Coupled Integral PINN for conservation law—0
Stationary Velocity Fields on Matrix Groups for Deformable Image Registration—0
Neurally Integrated Finite Elements for Differentiable Elasticity on Evolving Domains—0
GreenLight-Gym: Reinforcement learning benchmark environment for control of greenhouse production systemsCode1
Spectral Densities, Structured Noise and Ensemble Averaging within Open Quantum Dynamics—0
Average Causal Effect Estimation in DAGs with Hidden Variables: Extensions of Back-Door and Front-Door CriteriaCode0
Modelling the age distribution of longevity leaders—0
Correlation Properties in Channels with von Mises-Fisher Distribution of Scatterers—0
Domain-decoupled Physics-informed Neural Networks with Closed-form Gradients for Fast Model Learning of Dynamical Systems—0
Physics-informed nonlinear vector autoregressive models for the prediction of dynamical systemsCode0
Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning—0
An Efficient Approach to Regression Problems with Tensor Neural Networks—0
Flow map matching with stochastic interpolants: A mathematical framework for consistency models—0
A novel robust meta-analysis model using the t distribution for outlier accommodation and detection—0
Improving the Training of Rectified FlowsCode2
Exploration of methods for computing sensitivities in ODE models at dynamic and steady states—0
Message-Passing Monte Carlo: Generating low-discrepancy point sets via Graph Neural NetworksCode1
Identifiability of Differential-Algebraic SystemsCode0
Evaluating AI-generated code for C++, Fortran, Go, Java, Julia, Matlab, Python, R, and RustCode0
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