Covariance-Informed Subspace: an Adaptive Gradient-Free Input Dimension Reduction Method for Bayesian Inference
Fuente:
arXiv
Saved in:
| Main Authors: | Polette, Nadège, Maître, Olivier Le, Sochala, Pierre, Gesret, Alexandrine |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Change of Measure for Bayesian Field Inversion with Hierarchical Hyperparameters Sampling
by: Polette, Nadège, et al.
Published: (2024)
by: Polette, Nadège, et al.
Published: (2024)
Mode-wise Principal Subspace Pursuit and Matrix Spiked Covariance Model
by: Tang, Runshi, et al.
Published: (2023)
by: Tang, Runshi, et al.
Published: (2023)
Bayesian Nonparametric Inference in McKean-Vlasov models
by: Nickl, Richard, et al.
Published: (2024)
by: Nickl, Richard, et al.
Published: (2024)
Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
by: Li, Gen, et al.
Published: (2025)
by: Li, Gen, et al.
Published: (2025)
Covariance estimation using h-statistics in Monte Carlo and multilevel Monte Carlo methods
by: Shivanand, Sharana Kumar
Published: (2023)
by: Shivanand, Sharana Kumar
Published: (2023)
Posterior Concentration of Bayesian Physics-Informed Neural Networks for Elliptic PDEs
by: Zhao, Yuxuan, et al.
Published: (2026)
by: Zhao, Yuxuan, et al.
Published: (2026)
Benign overfitting in Fixed Dimension via Physics-Informed Learning with Smooth Inductive Bias
by: Wong, Honam, et al.
Published: (2024)
by: Wong, Honam, et al.
Published: (2024)
Posterior Covariance Structures in Gaussian Processes
by: Cai, Difeng, et al.
Published: (2024)
by: Cai, Difeng, et al.
Published: (2024)
A global Lipschitz stability perspective for understanding approximate approaches in Bayesian sequential learning
by: Wang, Liliang, et al.
Published: (2025)
by: Wang, Liliang, et al.
Published: (2025)
Convergence of Noise-Free Sampling Algorithms with Regularized Wasserstein Proximals
by: Han, Fuqun, et al.
Published: (2024)
by: Han, Fuqun, et al.
Published: (2024)
Extreme learning machines for variance-based global sensitivity analysis
by: Darges, John, et al.
Published: (2022)
by: Darges, John, et al.
Published: (2022)
Inhomogeneous Priors for Bayesian Inverse Problems
by: Afkham, Babak Maboudi, et al.
Published: (2026)
by: Afkham, Babak Maboudi, et al.
Published: (2026)
Adaptive minimax optimality in statistical inverse problems via SOLIT -- Sharp Optimal Lepskii-Inspired Tuning
by: Li, Housen, et al.
Published: (2023)
by: Li, Housen, et al.
Published: (2023)
Nonparametric Bayesian inference for reversible multi-dimensional diffusions
by: Giordano, Matteo, et al.
Published: (2020)
by: Giordano, Matteo, et al.
Published: (2020)
Extrapolation and generative algorithms for three applications in finance
by: LeFloch, Philippe G., et al.
Published: (2024)
by: LeFloch, Philippe G., et al.
Published: (2024)
Sequential multiple importance sampling for high-dimensional Bayesian inference
by: Binbin, Li, et al.
Published: (2025)
by: Binbin, Li, et al.
Published: (2025)
Accelerating Langevin Monte Carlo via Efficient Stochastic Runge--Kutta Methods beyond Log-Concavity
by: Yang, Bin, et al.
Published: (2026)
by: Yang, Bin, et al.
Published: (2026)
Ensemble Data Assimilation for Particle-based Methods
by: Duvillard, Marius, et al.
Published: (2024)
by: Duvillard, Marius, et al.
Published: (2024)
Reproducing kernel methods for machine learning, PDEs, and statistics
by: LeFloch, Philippe G., et al.
Published: (2024)
by: LeFloch, Philippe G., et al.
Published: (2024)
Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions
by: Lai, Peiyao, et al.
Published: (2024)
by: Lai, Peiyao, et al.
Published: (2024)
Solving PDEs on Spheres with Physics-Informed Convolutional Neural Networks
by: Lei, Guanhang, et al.
Published: (2023)
by: Lei, Guanhang, et al.
Published: (2023)
Non-Asymptotic Analysis of Ensemble Kalman Updates: Effective Dimension and Localization
by: Ghattas, Omar Al, et al.
Published: (2022)
by: Ghattas, Omar Al, et al.
Published: (2022)
Stein transport for Bayesian inference
by: Nüsken, Nikolas
Published: (2024)
by: Nüsken, Nikolas
Published: (2024)
Regularized Stein Variational Gradient Flow
by: He, Ye, et al.
Published: (2022)
by: He, Ye, et al.
Published: (2022)
High-order Accurate Inference on Manifolds
by: Huang, Chengzhu, et al.
Published: (2025)
by: Huang, Chengzhu, et al.
Published: (2025)
Provable Diffusion Posterior Sampling for Bayesian Inversion
by: Chang, Jinyuan, et al.
Published: (2025)
by: Chang, Jinyuan, et al.
Published: (2025)
A Closed-Form Transition Density Expansion for Elliptic and Hypo-Elliptic SDEs
by: Iguchi, Yuga, et al.
Published: (2025)
by: Iguchi, Yuga, et al.
Published: (2025)
Boosted optimal weighted least-squares
by: Haberstich, Cécile, et al.
Published: (2019)
by: Haberstich, Cécile, et al.
Published: (2019)
Strong consistency of an estimator by the truncated singular value decomposition for an errors-in-variables regression model with collinearity
by: Aishima, Kensuke
Published: (2023)
by: Aishima, Kensuke
Published: (2023)
One-dimensional Tensor Network Recovery
by: Chen, Ziang, et al.
Published: (2022)
by: Chen, Ziang, et al.
Published: (2022)
Blind free deconvolution over one-parameter sparse families via eigenmatrix
by: Ying, Lexing
Published: (2025)
by: Ying, Lexing
Published: (2025)
A polynomial chaos approach for uncertainty quantification of Monte Carlo transport codes
by: Geraci, Gianluca, et al.
Published: (2024)
by: Geraci, Gianluca, et al.
Published: (2024)
Computable error bounds for quasi-Monte Carlo using points with non-negative local discrepancy
by: Gnewuch, Michael, et al.
Published: (2023)
by: Gnewuch, Michael, et al.
Published: (2023)
On the contraction rate of the posterior distribution for nonlinear PDE parameter identification
by: Fan, Yuxin, et al.
Published: (2026)
by: Fan, Yuxin, et al.
Published: (2026)
Multi-fidelity No-U-Turn Sampling
by: Ravi, Kislaya, et al.
Published: (2023)
by: Ravi, Kislaya, et al.
Published: (2023)
Coverage errors for Student's t confidence intervals comparable to those in Hall (1988)
by: Owen, Art B.
Published: (2025)
by: Owen, Art B.
Published: (2025)
A Fourier-based inference method for learning interaction kernels in particle systems
by: Pavliotis, Grigorios A., et al.
Published: (2025)
by: Pavliotis, Grigorios A., et al.
Published: (2025)
An Approximation Theory Framework for Measure-Transport Sampling Algorithms
by: Baptista, Ricardo, et al.
Published: (2023)
by: Baptista, Ricardo, et al.
Published: (2023)
Sparse free deconvolution under unknown noise level via eigenmatrix
by: Ying, Lexing
Published: (2025)
by: Ying, Lexing
Published: (2025)
Tensor-train methods for sequential state and parameter learning in state-space models
by: Zhao, Yiran, et al.
Published: (2023)
by: Zhao, Yiran, et al.
Published: (2023)
Similar Items
-
Change of Measure for Bayesian Field Inversion with Hierarchical Hyperparameters Sampling
by: Polette, Nadège, et al.
Published: (2024) -
Mode-wise Principal Subspace Pursuit and Matrix Spiked Covariance Model
by: Tang, Runshi, et al.
Published: (2023) -
Bayesian Nonparametric Inference in McKean-Vlasov models
by: Nickl, Richard, et al.
Published: (2024) -
Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
by: Li, Gen, et al.
Published: (2025) -
Covariance estimation using h-statistics in Monte Carlo and multilevel Monte Carlo methods
by: Shivanand, Sharana Kumar
Published: (2023)