A supervised deep learning method for nonparametric density estimation
Fuente:
arXiv
Saved in:
| Main Authors: | Bos, Thijs, Schmidt-Hieber, Johannes |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Frontiers to the learning of nonparametric hidden Markov models
by: Abraham, Kweku, et al.
Published: (2023)
by: Abraham, Kweku, et al.
Published: (2023)
Nonparametric estimation of a factorizable density using diffusion models
by: Kwon, Hyeok Kyu, et al.
Published: (2025)
by: Kwon, Hyeok Kyu, et al.
Published: (2025)
Convergence guarantees for forward gradient descent in the linear regression model
by: Bos, Thijs, et al.
Published: (2023)
by: Bos, Thijs, et al.
Published: (2023)
The Optimality of Kernel Classifiers in Sobolev Space
by: Lai, Jianfa, et al.
Published: (2024)
by: Lai, Jianfa, et al.
Published: (2024)
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)
Distribution estimation via Flow Matching with Lipschitz guarantees
by: Kunkel, Lea
Published: (2025)
by: Kunkel, Lea
Published: (2025)
Quadratic functional estimation from observations with multiplicative measurement error
by: Neubert, Bianca, et al.
Published: (2024)
by: Neubert, Bianca, et al.
Published: (2024)
Tweedie-based nonparametric estimation for semicontinuous mixed densities
by: Lyu, Guanjie, et al.
Published: (2026)
by: Lyu, Guanjie, et al.
Published: (2026)
A hybrid-Hill estimator enabled by heavy-tailed block maxima
by: Neves, Claudia, et al.
Published: (2025)
by: Neves, Claudia, et al.
Published: (2025)
Maximum smoothed likelihood method for the combination of multiple diagnostic tests, with application to the ROC estimation
by: Zheng, Fangyong, et al.
Published: (2026)
by: Zheng, Fangyong, et al.
Published: (2026)
Adaptive estimation for nonparametric circular regression with errors in variables
by: Nguyen, Tien Dat, et al.
Published: (2025)
by: Nguyen, Tien Dat, et al.
Published: (2025)
Robust density estimation with the $\mathbb{L}_{1}$-loss. Applications to the estimation of a density on the line satisfying a shape constraint
by: Baraud, Y., et al.
Published: (2022)
by: Baraud, Y., et al.
Published: (2022)
Nonparametric Bayesian Inference for Stochastic Reaction-Diffusion Equations
by: Altmeyer, Randolf, et al.
Published: (2025)
by: Altmeyer, Randolf, et al.
Published: (2025)
Tensor Factor Model Estimation by Iterative Projection
by: Han, Yuefeng, et al.
Published: (2020)
by: Han, Yuefeng, et al.
Published: (2020)
Estimating a density near an unknown manifold: a Bayesian nonparametric approach
by: Berenfeld, Clément, et al.
Published: (2022)
by: Berenfeld, Clément, et al.
Published: (2022)
Dimension free ridge regression
by: Cheng, Chen, et al.
Published: (2022)
by: Cheng, Chen, et al.
Published: (2022)
Optimal estimation of a factorizable density using diffusion models with ReLU neural networks
by: Fan, Jianqing, et al.
Published: (2025)
by: Fan, Jianqing, et al.
Published: (2025)
Subordinated Wright-Fisher Priors
by: Judd, Nathan A., et al.
Published: (2026)
by: Judd, Nathan A., et al.
Published: (2026)
Mode-based estimation of the center of symmetry
by: Chacón, José E., et al.
Published: (2024)
by: Chacón, José E., et al.
Published: (2024)
Density estimation using the perceptron
by: Gerber, Patrik Róbert, et al.
Published: (2023)
by: Gerber, Patrik Róbert, et al.
Published: (2023)
A nonparametric test for elliptical distribution based on kernel embedding of probabilities
by: Tang, Yin, et al.
Published: (2023)
by: Tang, Yin, 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)
Efficient and Minimax Optimal In-context Nonparametric Regression with Transformers
by: Ching, Michelle, et al.
Published: (2026)
by: Ching, Michelle, et al.
Published: (2026)
Optimal In-context Adaptivity and Distributional Robustness of Transformers
by: Ma, Tianyi, et al.
Published: (2025)
by: Ma, Tianyi, et al.
Published: (2025)
Composite Lp-quantile regression, near quantile regression and the oracle model selection theory
by: Mou, Fuming Lin WEilin
Published: (2025)
by: Mou, Fuming Lin WEilin
Published: (2025)
The minimax optimal convergence rate of posterior density in the weighted orthogonal polynomials
by: Luo, Yiqi, et al.
Published: (2026)
by: Luo, Yiqi, et al.
Published: (2026)
Kernel density estimation with polyspherical data and its applications
by: García-Portugués, Eduardo, et al.
Published: (2024)
by: García-Portugués, Eduardo, et al.
Published: (2024)
On nonparametric estimation of the interaction function in particle system models
by: Belomestny, Denis, et al.
Published: (2024)
by: Belomestny, Denis, et al.
Published: (2024)
Identifying Network Hubs with the Partial Correlation Graphical LASSO
by: Bogdan, Małgorzata, et al.
Published: (2025)
by: Bogdan, Małgorzata, et al.
Published: (2025)
The Cost of Adaptation under Differential Privacy: Optimal Adaptive Federated Density Estimation
by: Cai, T. Tony, et al.
Published: (2025)
by: Cai, T. Tony, et al.
Published: (2025)
Improving variable selection properties with data integration and transfer learning
by: Rognon-Vael, Paul, et al.
Published: (2025)
by: Rognon-Vael, Paul, et al.
Published: (2025)
A Wasserstein perspective of Vanilla GANs
by: Kunkel, Lea, et al.
Published: (2024)
by: Kunkel, Lea, et al.
Published: (2024)
Goodness-of-fit testing from observations with multiplicative measurement error
by: Johannes, Jan, et al.
Published: (2025)
by: Johannes, Jan, et al.
Published: (2025)
Regularized least squares learning with heavy-tailed noise is minimax optimal
by: Mollenhauer, Mattes, et al.
Published: (2025)
by: Mollenhauer, Mattes, 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)
Lower Complexity Adaptation for Empirical Entropic Optimal Transport
by: Groppe, Michel, et al.
Published: (2023)
by: Groppe, Michel, et al.
Published: (2023)
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)
Convergence rates of non-stationary and deep Gaussian process regression
by: Osborne, Conor, et al.
Published: (2023)
by: Osborne, Conor, et al.
Published: (2023)
Maximum Likelihood Estimation of Nonnegative Trigonometric Sum Models Using a Newton-like Algorithm on Manifolds
by: Fernández-Durán, et al.
Published: (2010)
by: Fernández-Durán, et al.
Published: (2010)
Sharp Convergence Rates of Empirical Unbalanced Optimal Transport for Spatio-Temporal Point Processes
by: Struleva, Marina, et al.
Published: (2025)
by: Struleva, Marina, et al.
Published: (2025)
Similar Items
-
Frontiers to the learning of nonparametric hidden Markov models
by: Abraham, Kweku, et al.
Published: (2023) -
Nonparametric estimation of a factorizable density using diffusion models
by: Kwon, Hyeok Kyu, et al.
Published: (2025) -
Convergence guarantees for forward gradient descent in the linear regression model
by: Bos, Thijs, et al.
Published: (2023) -
The Optimality of Kernel Classifiers in Sobolev Space
by: Lai, Jianfa, et al.
Published: (2024) -
On the minimax optimality of Flow Matching through the connection to kernel density estimation
by: Kunkel, Lea, et al.
Published: (2025)