numerical integration

Hierarchical Bayesian Quadrature UAI 2026 Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling JMLR 2025 FNIN: A Fourier Neural Operator-based Numerical Integration Network for Surface-from-gradients AAAI 2025 Fast Fourier Bayesian Quadrature AISTATS 2024 Probabilistic ODE solvers for integration error-aware numerical optimal control L4DC 2024 Stability-Informed Initialization of Neural Ordinary Differential Equations ICML 2024 The Impact of Integration Step on Integrated Gradients EACL 2024 Kernel Quadrature with Randomly Pivoted Cholesky NeurIPS 2023 Generalized Bayesian quadrature with spectral kernels UAI 2022 Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks ICML 2022 On Numerical Integration in Neural Ordinary Differential Equations ICML 2022 Positively Weighted Kernel Quadrature via Subsampling NeurIPS 2022 Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs IJCAI 2022 An analysis of Ermakov-Zolotukhin quadrature using kernels NeurIPS 2021 AutoInt: Automatic Integration for Fast Neural Volume Rendering CVPR 2021 Bayesian Quadrature on Riemannian Data Manifolds ICML 2021 Estimation of Spectral Risk Measures AAAI 2021 Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model AISTATS 2021 Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization AISTATS 2021 A Locally Adaptive Bayesian Cubature Method AISTATS 2020 Analog Accelerator for Simulation and Diagnostics AAAI 2020 Bayesian Probabilistic Numerical Integration with Tree-Based Models NeurIPS 2020 On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method NeurIPS 2020 Subgroup-based Rank-1 Lattice Quasi-Monte Carlo NeurIPS 2020 Training Generative Adversarial Networks by Solving Ordinary Differential Equations NeurIPS 2020