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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 51–100 of 242 papers

TitleStatusHype
A note on the option price and 'Mass at zero in the uncorrelated SABR model and implied volatility asymptotics'Code0
On Numerical Integration in Neural Ordinary Differential EquationsCode0
Predicting Change, Not States: An Alternate Framework for Neural PDE SurrogatesCode0
Efficient time stepping for numerical integration using reinforcement learningCode0
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores SamplingCode0
Learning Nonparametric Volterra Kernels with Gaussian ProcessesCode0
Learning effective stochastic differential equations from microscopic simulations: linking stochastic numerics to deep learningCode0
Evaluating AI-generated code for C++, Fortran, Go, Java, Julia, Matlab, Python, R, and RustCode0
Learning Survival Distribution with Implicit Survival FunctionCode0
Machine Learning for the identification of phase-transitions in interacting agent-based systems: a Desai-Zwanzig exampleCode0
Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-β signalingCode0
How Far Are We from Optimal Reasoning Efficiency?Code0
Average Causal Effect Estimation in DAGs with Hidden Variables: Extensions of Back-Door and Front-Door CriteriaCode0
Identifiability of Differential-Algebraic SystemsCode0
Designing Stable Neural Networks using Convex Analysis and ODEsCode0
Discretization Invariant Networks for Learning Maps between Neural FieldsCode0
Adaptive Process-Guided Learning: An Application in Predicting Lake DO ConcentrationsCode0
i-flow: High-dimensional Integration and Sampling with Normalizing FlowsCode0
Batch Selection for Parallelisation of Bayesian QuadratureCode0
Distributional Gradient Matching for Learning Uncertain Neural Dynamics ModelsCode0
Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps—0
Auto-Calibration and 2D-DOA Estimation in UCAs via an Integrated Wideband Dictionary—0
Data-Augmented Numerical Integration in State Prediction: Rule Selection—0
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory—0
Revisiting the Effects of Stochasticity for Hamiltonian Samplers—0
A monotone piecewise constant control integration approach for the two-factor uncertain volatility model—0
Coupled Integral PINN for conservation law—0
Correlation Properties in Channels with von Mises-Fisher Distribution of Scatterers—0
Convergence guarantees for kernel-based quadrature rules in misspecified settings—0
Convergence Guarantees for Adaptive Bayesian Quadrature Methods—0
A monotone numerical integration method for mean-variance portfolio optimization under jump-diffusion models—0
Adaptive approximation of monotone functions—0
Continuous-time iterative linear-quadratic regulator—0
Asian Option Pricing with Orthogonal Polynomials—0
Constructing Low Star Discrepancy Point Sets with Genetic Algorithms—0
Asian Basket Spread Options: A New Approximation Based on Stochastic Taylor Expansions—0
All-Action Policy Gradient Methods: A Numerical Integration Approach—0
Gaussian Processes and Reproducing Kernels: Connections and Equivalences—0
Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation—0
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms—0
Flow map matching with stochastic interpolants: A mathematical framework for consistency models—0
Computing Modes of Instability of Parameterized Nonlinear Systems for Vulnerability Assessment—0
Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space—0
Active Learning of Model Evidence Using Bayesian Quadrature—0
A Closed-Form Approximation of the Gaussian Noise Model in the Presence of Inter-Channel Stimulated Raman Scattering—0
Flow Segmentation in Dense Crowds—0
Flow-based density of states for complex actions—0
Fitting mixed logit random regret minimization models using maximum simulated likelihood—0
Accurate and efficient Simulation of very high-dimensional Neural Mass Models with distributed-delay Connectome Tensors—0
Least-Squares Neural Network (LSNN) Method For Scalar Nonlinear Hyperbolic Conservation Laws: Discrete Divergence Operator—0
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