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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 101–150 of 242 papers

TitleStatusHype
Bayesian Experimental Design for Symbolic Discovery—0
Learning Integrable Dynamics with Action-Angle NetworksCode1
A Quantum-Powered Photorealistic Rendering—0
Geometry-preserving Lie Group Integrators For Differential Equations On The Manifold Of Symmetric Positive Definite Matrices—0
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein DistancesCode0
Optimization-Informed Neural Networks—0
ProDMPs: A Unified Perspective on Dynamic and Probabilistic Movement Primitives—0
Continuous Mixtures of Tractable Probabilistic ModelsCode1
Novel predator-prey model admitting exact analytical solution—0
On Numerical Integration in Neural Ordinary Differential EquationsCode0
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel RecombinationCode1
Discretization Invariant Networks for Learning Maps between Neural FieldsCode0
Sampling-free Inference for Ab-Initio Potential Energy Surface NetworksCode1
Implicit Function Theorem: Estimates on the size of the domain—0
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNsCode0
Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power SystemCode1
Flow-based density of states for complex actions—0
What ODE-Approximation Schemes of Time-Delay Systems Reveal about Lyapunov-Krasovskii Functionals—0
Splitting numerical integration for matrix completion—0
Fenrir: Physics-Enhanced Regression for Initial Value ProblemsCode0
Inertial Navigation Using an Inertial Sensor ArrayCode0
Mars Entry Trajectory Planning with Range Discretization and Successive Convexification—0
Small-Signal Stability Analysis of Numerical Integration Methods—0
Learned Cone-Beam CT Reconstruction Using Neural Ordinary Differential Equations—0
Machine learning prediction for mean motion resonance behaviour -- The planar case—0
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEsCode0
`Next Generation' Reservoir Computing: an Empirical Data-Driven Expression of Dynamical Equations in Time-Stepping Form—0
Invariant Priors for Bayesian Quadrature—0
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel—0
Numerical Smoothing with Hierarchical Adaptive Sparse Grids and Quasi-Monte Carlo Methods for Efficient Option Pricing—0
Small-Signal Stability Techniques for Power System Modal Analysis, Control, and Numerical Integration—0
A Frequency Domain Approach to Predict Power System TransientsCode1
Feasibility Study of Neural ODE and DAE Modules for Power System Dynamic Component ModelingCode1
Least-Squares Neural Network (LSNN) Method For Scalar Nonlinear Hyperbolic Conservation Laws: Discrete Divergence Operator—0
Extracting Dynamical Models from Data—0
Efficient Modeling of Morphing Wing Flight Using Neural Networks and Cubature Rules—0
Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit—0
Learning Dynamics from Noisy Measurements using Deep Learning with a Runge-Kutta Constraint—0
Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-β signalingCode0
Revisiting the Effects of Stochasticity for Hamiltonian Samplers—0
Distributional Gradient Matching for Learning Uncertain Neural Dynamics ModelsCode0
Learning effective stochastic differential equations from microscopic simulations: linking stochastic numerics to deep learningCode0
Learning Nonparametric Volterra Kernels with Gaussian ProcessesCode0
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
Discovery of Nonlinear Dynamical Systems using a Runge-Kutta Inspired Dictionary-based Sparse Regression ApproachCode1
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
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