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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 51–75 of 242 papers

TitleStatusHype
Constructing Low Star Discrepancy Point Sets with Genetic Algorithms—0
Lilan: A linear latent network approach for real-time solutions of stiff, nonlinear, ordinary differential equations—0
A novel robust meta-analysis model using the t distribution for outlier accommodation and detection—0
Continuous-time iterative linear-quadratic regulator—0
Convergence Guarantees for Adaptive Bayesian Quadrature Methods—0
Convergence guarantees for kernel-based quadrature rules in misspecified settings—0
Correlation Properties in Channels with von Mises-Fisher Distribution of Scatterers—0
Coupled Integral PINN for conservation law—0
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory—0
Data-Augmented Numerical Integration in State Prediction: Rule Selection—0
Auto-Calibration and 2D-DOA Estimation in UCAs via an Integrated Wideband Dictionary—0
Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps—0
Fast Approximate Bayesian Computation for Estimating Parameters in Differential Equations—0
Bounds and Approximations for the Distribution of a Sum of Lognormal Random Variables—0
Beyond Monte Carlo: Harnessing Diffusion Models to Simulate Financial Market Dynamics—0
A note on the option price and 'Mass at zero in the uncorrelated SABR model and implied volatility asymptotics'—0
Fast Empirical Scenarios—0
Adaptive quadrature schemes for Bayesian inference via active learning—0
A Neural ODE Interpretation of Transformer Layers—0
Exploration of methods for computing sensitivities in ODE models at dynamic and steady states—0
Efficient Modeling of Morphing Wing Flight Using Neural Networks and Cubature Rules—0
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features—0
Domain-decoupled Physics-informed Neural Networks with Closed-form Gradients for Fast Model Learning of Dynamical Systems—0
Bayesian Experimental Design for Symbolic Discovery—0
An Equivalent Circuit Approach to Distributed Optimization—0
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