Cover Image

Calibrated Generalized Bayesian Inference

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Frazier, David T., Drovandi, Christopher, Kohn, Robert
Format:	Preprint
Published:	2023
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Robustifying Approximate Bayesian Computation
by: Weerasinghe, Chaya, et al.
Published: (2025)

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

Synthetic likelihood in misspecified models
by: Frazier, David T., et al.
Published: (2021)

Exact Sampling of Gibbs Measures with Estimated Losses
by: Frazier, David T., et al.
Published: (2024)

Pooling information in likelihood-free inference
by: Frazier, David T., et al.
Published: (2022)

Simulation-based Bayesian inference under model misspecification
by: Kelly, Ryan P., et al.
Published: (2025)

Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference
by: Kelly, Ryan P., et al.
Published: (2023)

Bayesian inference for ordinary differential equations models with heteroscedastic measurement error
by: Salimi, Selva, et al.
Published: (2026)

Preconditioned Robust Neural Posterior Estimation for Misspecified Simulators
by: Kelly, Ryan P., et al.
Published: (2026)

Calibrating Bayesian Inference
by: Liu, Yang, et al.
Published: (2025)

Probabilistic Predictions of Option Prices with Modular Approximate Bayesian Inference
by: Maneesoonthorn, Worapree, et al.
Published: (2024)

Bayesian score calibration for approximate models
by: Bon, Joshua J, et al.
Published: (2022)

Calibrated Bayesian inference for random fields on large irregular domains using the debiased spatial Whittle likelihood
by: Goodwin, Thomas, et al.
Published: (2025)

Bayesian Modular Inference for Copula Models with Potentially Misspecified Marginals
by: Kock, Lucas, et al.
Published: (2026)

Spectral domain likelihoods for Bayesian inference in time-varying parameter models
by: Gustafsson, Oskar, et al.
Published: (2024)

Posterior risk of modular and semi-modular Bayesian inference
by: Frazier, David T., et al.
Published: (2023)

Accelerating sequential Monte Carlo with surrogate likelihoods
by: Bon, Joshua J, et al.
Published: (2020)

Beyond data: leveraging non-empirical information and expert knowledge in Bayesian model calibration
by: Vollert, Sarah A., et al.
Published: (2025)

Calibrated Bayesian Nonparametric Tolerance Intervals
by: Pourmohamad, Tony, et al.
Published: (2026)

Fast Variational Boosting for Latent Variable Models
by: Gunawan, David, et al.
Published: (2025)

On the Stability of General Bayesian Inference
by: Jewson, Jack, et al.
Published: (2023)

A Beta Cauchy-Cauchy (BECCA) shrinkage prior for Bayesian variable selection
by: Rodrigo, Linduni M., et al.
Published: (2025)

Bias Mitigation in Matched Observational Studies with Continuous Treatments: Calipered Non-Bipartite Matching and Bias-Corrected Estimation and Inference
by: Frazier, Anthony, et al.
Published: (2024)

A Principled Approach to Bayesian Transfer Learning
by: Bretherton, Adam, et al.
Published: (2025)

Generalized Bayesian Likelihood-Free Inference
by: Pacchiardi, Lorenzo, et al.
Published: (2021)

Time-Varying Multi-Seasonal AR Models
by: Fagerberg, Ganna, et al.
Published: (2024)

Bayesian Inference for Single-factor Graphical Models
by: Marcano, David, et al.
Published: (2025)

A General Framework for Cutting Feedback within Modularised Bayesian Inference
by: Liu, Yang, et al.
Published: (2022)

Sequential Scoring Rule Evaluation for Forecast Method Selection
by: Frazier, David T., et al.
Published: (2025)

Elastic Bayesian Model Calibration
by: Francom, Devin, et al.
Published: (2023)

Generative Bayesian Inference with GANs
by: Wang, Yuexi, et al.
Published: (2022)

Dynamic linear regression models for forecasting time series with semi long memory errors
by: Goodwin, Thomas, et al.
Published: (2024)

Fiducial Inference for Random-Effects Calibration Models: Advancing Reliable Quantification in Environmental Analytical Chemistry
by: Sahu, Soumya, et al.
Published: (2025)

Stochastic Approximation Cut Algorithm for Inference in Modularized Bayesian Models
by: Liu, Yang, et al.
Published: (2020)

Anomaly detection using surprisals
by: Hyndman, Rob J, et al.
Published: (2026)

Calibrating hierarchical Bayesian domain inference for a proportion
by: Lei, Rayleigh, et al.
Published: (2025)

Bayesian Inference for Non-Gaussian Simultaneous Autoregressive Models with Missing Data
by: Wijayawardhana, Anjana, et al.
Published: (2025)

The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
by: Thompson, Ryan, et al.
Published: (2023)

Generalized Bayesian Inference for Dynamic Random Dot Product Graphs
by: Loyal, Joshua Daniel
Published: (2025)

Outcome-Calibrated Regression and Predicted Outcome-Based Inference
by: Lee, Hwiyoung, et al.
Published: (2026)