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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 151–175 of 242 papers

TitleStatusHype
Learning Nonparametric Volterra Kernels with Gaussian ProcessesCode0
Learning effective stochastic differential equations from microscopic simulations: linking stochastic numerics to deep learningCode0
Power System Transient Modeling and Simulation using Integrated Circuit—0
MAGI-X: Manifold-Constrained Gaussian Process Inference for Unknown System Dynamics—0
Least-Squares ReLU Neural Network (LSNN) Method For Scalar Nonlinear Hyperbolic Conservation Law—0
Normal Tempered Stable Processes and the Pricing of Energy Derivatives—0
The mixed deep energy method for resolving concentration features in finite strain hyperelasticity—0
Efficient time stepping for numerical integration using reinforcement learningCode0
BoXHED2.0: Scalable boosting of dynamic survival analysisCode0
Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps—0
Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization—0
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems—0
Differentiable Implicit Soft-Body Physics—0
A Renormalization Group Approach to Connect Discrete- and Continuous-Time Descriptions of Gaussian Processes—0
Gauss-Legendre Features for Gaussian Process Regression—0
Efficient Solution of Boolean Satisfiability Problems with Digital MemComputing—0
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method—0
Towards a Unified Quadrature Framework for Large-Scale Kernel Machines—0
A note on the option price and 'Mass at zero in the uncorrelated SABR model and implied volatility asymptotics'—0
Numerical Predictive Control for Delay Compensation—0
Accurate and efficient Simulation of very high-dimensional Neural Mass Models with distributed-delay Connectome Tensors—0
Symplectic Gaussian Process Regression of Hamiltonian Flow Maps—0
Ridge Regression with Over-Parametrized Two-Layer Networks Converge to Ridgelet Spectrum—0
Complete dimensional collapse in the continuum limit of a delayed SEIQR network model with separable distributed infectivity—0
PECAIQR: A Model for Infectious Disease Applied to the Covid-19 Epidemic—0
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