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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 201–225 of 242 papers

TitleStatusHype
Inertial Navigation Using an Inertial Sensor ArrayCode0
Efficient time stepping for numerical integration using reinforcement learningCode0
Scalable Variational Inference for Dynamical SystemsCode0
On Numerical Integration in Neural Ordinary Differential EquationsCode0
A hybrid approach for solving the gravitational N-body problem with Artificial Neural NetworksCode0
Evaluating AI-generated code for C++, Fortran, Go, Java, Julia, Matlab, Python, R, and RustCode0
AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEsCode0
A Dictionary of Closed-Form Kernel Mean EmbeddingsCode0
Provable Quantum Algorithm Advantage for Gaussian Process QuadratureCode0
Stability-Informed Initialization of Neural Ordinary Differential EquationsCode0
Distributional Gradient Matching for Learning Uncertain Neural Dynamics ModelsCode0
Quadrature-based features for kernel approximationCode0
Learning effective stochastic differential equations from microscopic simulations: linking stochastic numerics to deep learningCode0
BoXHED2.0: Scalable boosting of dynamic survival analysisCode0
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNsCode0
Fenrir: Physics-Enhanced Regression for Initial Value ProblemsCode0
Bayesian Probabilistic Numerical Integration with Tree-Based ModelsCode0
Bayesian Numerical Integration with Neural NetworksCode0
Learning Survival Distribution with Implicit Survival FunctionCode0
Learning Nonparametric Volterra Kernels with Gaussian ProcessesCode0
Average Causal Effect Estimation in DAGs with Hidden Variables: Extensions of Back-Door and Front-Door CriteriaCode0
Designing Stable Neural Networks using Convex Analysis and ODEsCode0
Discretization Invariant Networks for Learning Maps between Neural FieldsCode0
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein DistancesCode0
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEsCode0
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