Imagen de Portada

Robust Bayesian Inference via Variational Approximations of Generalized Rho-Posteriors

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Khribch, EL Mahdi, Alquier, Pierre
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Statistics Theory
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Convergence of Statistical Estimators via Mutual Information Bounds
por: Khribch, El Mahdi, et al.
Publicado: (2024)

User-friendly introduction to PAC-Bayes bounds
por: Alquier, Pierre
Publicado: (2021)

Variance-Aware Estimation of Kernel Mean Embedding
por: Wolfer, Geoffrey, et al.
Publicado: (2022)

An Equivalence between Bayesian Priors and Penalties in Variational Inference
por: Wolinski, Pierre, et al.
Publicado: (2020)

SPDE Methods for Nonparametric Bayesian Posterior Contraction and Laplace Approximation
por: Alberola-Boloix, Enric, et al.
Publicado: (2026)

Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence
por: Chérief-Abdellatif, Badr-Eddine, et al.
Publicado: (2019)

Rates of Convergence of Generalised Variational Inference Posteriors under Prior Misspecification
por: Mildner, Terje, et al.
Publicado: (2025)

Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference
por: Kungurtsev, Vyacheslav, et al.
Publicado: (2024)

Latent-IMH: Efficient Bayesian Inference for Inverse Problems with Approximate Operators
por: Chen, Youguang, et al.
Publicado: (2026)

Central Limit Theorem for Bayesian Neural Network trained with Variational Inference
por: Descours, Arnaud, et al.
Publicado: (2024)

On Reconstructing Training Data From Bayesian Posteriors and Trained Models
por: Wynne, George
Publicado: (2025)

AutoBayes: A Compositional Framework for Generalized Variational Inference
por: Smithe, Toby St Clere, et al.
Publicado: (2025)

Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity
por: Legramanti, Sirio, et al.
Publicado: (2022)

Generalized Power Priors for Improved Bayesian Inference with Historical Data
por: Kimura, Masanari, et al.
Publicado: (2025)

Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation
por: Wu, Bohan, et al.
Publicado: (2024)

Estimating the Number of Components in Finite Mixture Models via Variational Approximation
por: Wang, Chenyang, et al.
Publicado: (2024)

Counterfactual Generative Modeling with Variational Causal Inference
por: Wu, Yulun, et al.
Publicado: (2024)

On importance sampling and independent Metropolis-Hastings with an unbounded weight function
por: Deligiannidis, George, et al.
Publicado: (2024)

Frequentist Guarantees of Distributed (Non)-Bayesian Inference
por: Wu, Bohan, et al.
Publicado: (2023)

Conformal Prediction Under Generalized Covariate Shift with Posterior Drift
por: Wang, Baozhen, et al.
Publicado: (2025)

Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
por: Altekrüger, Fabian, et al.
Publicado: (2023)

Functional Bias and Tangent-Space Geometry in Variational Inference
por: Plummer, Sean
Publicado: (2026)

Meta-Posterior Consistency for the Bayesian Inference of Metastable System
por: Adams, Zachary P, et al.
Publicado: (2024)

Provable Diffusion Posterior Sampling for Bayesian Inversion
por: Chang, Jinyuan, et al.
Publicado: (2025)

Exact and Approximate Conformal Inference for Multi-Output Regression
por: Johnstone, Chancellor, et al.
Publicado: (2022)

Variational bagging: a robust approach for Bayesian uncertainty quantification
por: Fan, Shitao, et al.
Publicado: (2025)

Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effects
por: Sert, Gözde, et al.
Publicado: (2025)

Posterior Concentration of Bayesian Physics-Informed Neural Networks for Elliptic PDEs
por: Zhao, Yuxuan, et al.
Publicado: (2026)

Concentration and Calibration in Predictive Bayesian Inference
por: Frazier, David T., et al.
Publicado: (2026)

Variational Bayesian Bow tie Neural Networks with Shrinkage
por: Sheinkman, Alisa, et al.
Publicado: (2024)

Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression
por: Tan, Kai, et al.
Publicado: (2024)

Stability of Sequential and Parallel Coordinate Ascent Variational Inference
por: Pati, Debdeep
Publicado: (2026)

Optimistic Estimation of Convergence in Markov Chains with the Average-Mixing Time
por: Wolfer, Geoffrey, et al.
Publicado: (2024)

Bayesian Semi-supervised Inference via a Debiased Modeling Approach
por: Sert, Gözde, et al.
Publicado: (2025)

Bayesian Inference with Shaped Deep Non-linear MLPs
por: Hanin, Boris, et al.
Publicado: (2026)

Variational Causal Inference
por: Wu, Yulun, et al.
Publicado: (2022)

Variational inference via radial transport
por: Ghafourpour, Luca, et al.
Publicado: (2026)

Structured Optimal Variational Inference for Dynamic Latent Space Models
por: Zhao, Peng, et al.
Publicado: (2022)

ARK: Robust Knockoffs Inference with Coupling
por: Fan, Yingying, et al.
Publicado: (2023)

Minmax Trend Filtering: Generalizations of Total Variation Denoising via a Local Minmax/Maxmin Formula
por: Chatterjee, Sabyasachi
Publicado: (2024)