Saved in:
| Main Authors: | Ye, Ziyang, Tan, Haoyuan, Wang, Xiaoqun, He, Zhijian |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.15419 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Error Bounds for Importance Sampling with Estimated Proposal Distributions
by: Aeckerle-Willems, Cathrine, et al.
Published: (2026)
by: Aeckerle-Willems, Cathrine, et al.
Published: (2026)
An effective estimation of multivariate density functions using extended-beta kernels with Bayesian adaptive bandwidths
by: Somé, Sobom M., et al.
Published: (2025)
by: Somé, Sobom M., et al.
Published: (2025)
Density estimation for elliptic PDE with random input by preintegration and quasi-Monte Carlo methods
by: Gilbert, Alexander D., et al.
Published: (2024)
by: Gilbert, Alexander D., et al.
Published: (2024)
Kernel Density Estimation and Convolution Revisited
by: Tenkorang, Nicholas, et al.
Published: (2025)
by: Tenkorang, Nicholas, et al.
Published: (2025)
Kernel Density Machines
by: Della Vecchia, Andrea, et al.
Published: (2025)
by: Della Vecchia, Andrea, et al.
Published: (2025)
Adaptive joint distribution learning
by: Filipovic, Damir, et al.
Published: (2021)
by: Filipovic, Damir, et al.
Published: (2021)
ICS for complex data with application to outlier detection for density data
by: Mondon, Camille, et al.
Published: (2025)
by: Mondon, Camille, et al.
Published: (2025)
Quasi-Monte Carlo and importance sampling methods for Bayesian inverse problems
by: He, Zhijian, et al.
Published: (2024)
by: He, Zhijian, et al.
Published: (2024)
Lengthscale-informed sparse grids for kernel methods in high dimensions
by: Addy, Elliot J., et al.
Published: (2025)
by: Addy, Elliot J., et al.
Published: (2025)
Solving the inverse source problem of the fractional Poisson equation by MC-fPINNs
by: Sheng, Rui, et al.
Published: (2024)
by: Sheng, Rui, et al.
Published: (2024)
STM Image Analysis using Autoencoders
by: Binev, Peter, et al.
Published: (2025)
by: Binev, Peter, et al.
Published: (2025)
A Stabilized Physics Informed Neural Networks Method for Wave Equations
by: Jiao, Yuling, et al.
Published: (2024)
by: Jiao, Yuling, et al.
Published: (2024)
Splinets -- splines through the Taylor expansion, their support sets and orthogonal bases
by: Podgórski, Krzysztof
Published: (2021)
by: Podgórski, Krzysztof
Published: (2021)
An energy-based deep splitting method for the nonlinear filtering problem
by: Bågmark, Kasper, et al.
Published: (2022)
by: Bågmark, Kasper, et al.
Published: (2022)
Asymptotic properties of the normalized discrete associated-kernel estimator for probability mass function
by: Esstafa, Youssef, et al.
Published: (2022)
by: Esstafa, Youssef, et al.
Published: (2022)
Wavelet-Based Density Estimation for Persistent Homology
by: Häberle, Konstantin, et al.
Published: (2023)
by: Häberle, Konstantin, et al.
Published: (2023)
A deterministic multiple-shift lattice algorithm for function approximation in Korobov and half-period Cosine spaces
by: Du, Jiarui, et al.
Published: (2026)
by: Du, Jiarui, et al.
Published: (2026)
A Novel Hybrid Approach for Time Series Forecasting: Period Estimation and Climate Data Analysis Using Unsupervised Learning and Spline Interpolation
by: Kayal, Tanmay, et al.
Published: (2025)
by: Kayal, Tanmay, et al.
Published: (2025)
Density estimation using the perceptron
by: Gerber, Patrik Róbert, et al.
Published: (2023)
by: Gerber, Patrik Róbert, et al.
Published: (2023)
On the minimax optimality of Flow Matching through the connection to kernel density estimation
by: Kunkel, Lea, et al.
Published: (2025)
by: Kunkel, Lea, et al.
Published: (2025)
Minimax properties of gamma kernel density estimators under $L^p$ loss and $β$-Hölder smoothness of the target
by: Ouimet, Frédéric
Published: (2026)
by: Ouimet, Frédéric
Published: (2026)
Deterministic Fokker-Planck Transport -- With Applications to Sampling, Variational Inference, Kernel Mean Embeddings & Sequential Monte Carlo
by: Klebanov, Ilja
Published: (2024)
by: Klebanov, Ilja
Published: (2024)
Multiple combined gamma kernel estimations for nonnegative data with Bayesian adaptive bandwidths
by: Somé, Sobom M., et al.
Published: (2022)
by: Somé, Sobom M., et al.
Published: (2022)
Asymptotic normality and strong consistency of kernel regression estimation in q-calculus
by: Nkou, Emmanuel De Dieu, et al.
Published: (2025)
by: Nkou, Emmanuel De Dieu, et al.
Published: (2025)
Deep Neural Networks and Finite Elements of Any Order on Arbitrary Dimensions
by: He, Juncai, et al.
Published: (2023)
by: He, Juncai, et al.
Published: (2023)
High-dimensional Bayesian filtering through deep density approximation
by: Bågmark, Kasper, et al.
Published: (2025)
by: Bågmark, Kasper, et al.
Published: (2025)
Nonlinear filtering based on density approximation and deep BSDE prediction
by: Bågmark, Kasper, et al.
Published: (2025)
by: Bågmark, Kasper, et al.
Published: (2025)
Quasi-Monte Carlo for Bayesian design of experiment problems governed by parametric PDEs
by: Kaarnioja, Vesa, et al.
Published: (2024)
by: Kaarnioja, Vesa, et al.
Published: (2024)
Dirichlet kernel density estimation on the simplex with missing data
by: Daayeb, Hanen, et al.
Published: (2026)
by: Daayeb, Hanen, et al.
Published: (2026)
Operator Learning Using Random Features: A Tool for Scientific Computing
by: Nelsen, Nicholas H., et al.
Published: (2024)
by: Nelsen, Nicholas H., et al.
Published: (2024)
Alpha shapes in kernel density estimation
by: Carlsson, Erik, et al.
Published: (2023)
by: Carlsson, Erik, et al.
Published: (2023)
Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods
by: Jana, Soham, et al.
Published: (2022)
by: Jana, Soham, et al.
Published: (2022)
Error analysis for empirical risk minimization over clipped ReLU networks in solving linear Kolmogorov partial differential equations
by: Xiao, Jichang, et al.
Published: (2023)
by: Xiao, Jichang, et al.
Published: (2023)
Subspace accelerated measure transport methods for fast and scalable sequential experimental design, with application to photoacoustic imaging
by: Cui, Tiangang, et al.
Published: (2025)
by: Cui, Tiangang, et al.
Published: (2025)
A convergent scheme for the Bayesian filtering problem based on the Fokker--Planck equation and deep splitting
by: Bågmark, Kasper, et al.
Published: (2024)
by: Bågmark, Kasper, et al.
Published: (2024)
Separation rates for the detection of synchronization of interacting point processes in a mean field frame. Application to neuroscience
by: Tchouanti, Josué, et al.
Published: (2024)
by: Tchouanti, Josué, et al.
Published: (2024)
Analysis and conditional optimization of projection estimates for distribution of random variable using Legendre polynomials
by: Averina, Tatyana A., et al.
Published: (2025)
by: Averina, Tatyana A., et al.
Published: (2025)
A Distributions-based Approach for Data-Consistent Inversion
by: Bergstrom, Kirana, et al.
Published: (2024)
by: Bergstrom, Kirana, et al.
Published: (2024)
Efficient error estimators for Generalized Nyström
by: Lazzarino, Lorenzo, et al.
Published: (2026)
by: Lazzarino, Lorenzo, et al.
Published: (2026)
Non-asymptotic error estimates for the Laplace approximation in Bayesian inverse problems
by: Helin, Tapio, et al.
Published: (2020)
by: Helin, Tapio, et al.
Published: (2020)
Similar Items
-
Error Bounds for Importance Sampling with Estimated Proposal Distributions
by: Aeckerle-Willems, Cathrine, et al.
Published: (2026) -
An effective estimation of multivariate density functions using extended-beta kernels with Bayesian adaptive bandwidths
by: Somé, Sobom M., et al.
Published: (2025) -
Density estimation for elliptic PDE with random input by preintegration and quasi-Monte Carlo methods
by: Gilbert, Alexander D., et al.
Published: (2024) -
Kernel Density Estimation and Convolution Revisited
by: Tenkorang, Nicholas, et al.
Published: (2025) -
Kernel Density Machines
by: Della Vecchia, Andrea, et al.
Published: (2025)