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Numerical Integration
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Numerical integration is the task to calculate the numerical value of a definite integral or the numerical solution of differential equations.
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models
How Far Are We from Optimal Reasoning Efficiency?
ODE-GS: Latent ODEs for Dynamic Scene Extrapolation with 3D Gaussian Splatting
Operator-Splitting Methods for Neuromorphic Circuit Simulation
Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space
Continuous-time iterative linear-quadratic regulator
Discretization of Linear Systems using the Matrix Exponential
A Dictionary of Closed-Form Kernel Mean Embeddings
On the Eigenvalue Tracking of Large-Scale Systems
Asian Basket Spread Options: A New Approximation Based on Stochastic Taylor Expansions
Riemannian Patch Assignment Gradient Flows
Neural network-enhanced integrators for simulating ordinary differential equations
Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks
Computing Modes of Instability of Parameterized Nonlinear Systems for Vulnerability Assessment
PI-Controlled Variable Time-Step Power System Simulation Using an Adaptive Order Differential Transformation Method
Denoising Hamiltonian Network for Physical Reasoning
Underdamped Diffusion Bridges with Applications to Sampling
Provable Quantum Algorithm Advantage for Gaussian Process Quadrature
EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems
FNIN: A Fourier Neural Operator-based Numerical Integration Network for Surface-form-gradients
Lilan: A linear latent network approach for real-time solutions of stiff, nonlinear, ordinary differential equations
Median of Means Sampling for the Keister Function
Time-Reversible Bridges of Data with Machine Learning
Graph Spring Neural ODEs for Link Sign Prediction
Predicting Change, Not States: An Alternate Framework for Neural PDE Surrogates
Importance Sampling With Stochastic Particle Flow and Diffusion Optimization
Data-Augmented Numerical Integration in State Prediction: Rule Selection
Modular addition without black-boxes: Compressing explanations of MLPs that compute numerical integration
Beyond Monte Carlo: Harnessing Diffusion Models to Simulate Financial Market Dynamics
Adaptive Process-Guided Learning: An Application in Predicting Lake DO Concentrations
Coupled Integral PINN for conservation law
Stationary Velocity Fields on Matrix Groups for Deformable Image Registration
Neurally Integrated Finite Elements for Differentiable Elasticity on Evolving Domains
GreenLight-Gym: Reinforcement learning benchmark environment for control of greenhouse production systems
Spectral Densities, Structured Noise and Ensemble Averaging within Open Quantum Dynamics
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.