Cover Image

AutoBayes: A Compositional Framework for Generalized Variational Inference

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Smithe, Toby St Clere, Perin, Marco
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Copy-composition for Probabilistic Graphical Models
by: Smithe, Toby St Clere
Published: (2024)

Structured Active Inference (Extended Abstract)
by: Smithe, Toby St Clere
Published: (2024)

On the Functoriality of Belief Propagation Algorithms on finite Partially Ordered Sets
by: Sergeant-Perthuis, Grégoire, et al.
Published: (2025)

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

Robust Bayesian Inference via Variational Approximations of Generalized Rho-Posteriors
by: Khribch, EL Mahdi, et al.
Published: (2026)

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

Anytime-valid, Bayes-assisted, Prediction-Powered Inference
by: Kilian, Valentin, et al.
Published: (2025)

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

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

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

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

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

Variational Causal Inference
by: Wu, Yulun, et al.
Published: (2022)

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

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

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

Inference for Deep Neural Network Estimators in Generalized Nonparametric Models
by: Meng, Xuran, et al.
Published: (2025)

Deep Variational Multivariate Information Bottleneck -- A Framework for Variational Losses
by: Abdelaleem, Eslam, et al.
Published: (2023)

Bridging Maximum Likelihood and Optimal Transport for Efficient Inference and Model Selection in Stochastic Block Models
by: Queric, Simon, et al.
Published: (2026)

A Notion of Uniqueness for the Adversarial Bayes Classifier
by: Frank, Natalie S.
Published: (2024)

Variational Optimality of Föllmer Processes in Generative Diffusions
by: Chen, Yifan, et al.
Published: (2026)

A Unified Information-Theoretic Framework for Meta-Learning Generalization
by: Wen, Wen, et al.
Published: (2025)

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

Extended Fiducial Inference: Toward an Automated Process of Statistical Inference
by: Liang, Faming, et al.
Published: (2024)

General Frameworks for Conditional Two-Sample Testing
by: Lee, Seongchan, et al.
Published: (2024)

User-friendly introduction to PAC-Bayes bounds
by: Alquier, Pierre
Published: (2021)

Adaptive variational Bayes: Optimality, computation and applications
by: Ohn, Ilsang, et al.
Published: (2021)

Adversarial Consistency and the Uniqueness of the Adversarial Bayes Classifier
by: Frank, Natalie S.
Published: (2024)

Spectrum-Aware Debiasing: A Modern Inference Framework with Applications to Principal Components Regression
by: Li, Yufan, et al.
Published: (2023)

Variational inference via radial transport
by: Ghafourpour, Luca, et al.
Published: (2026)

Do More Predictions Improve Statistical Inference? Filtered Prediction-Powered Inference
by: Xu, Shirong, et al.
Published: (2026)

Conditional Predictive Inference for General Structured Data with Group Symmetries
by: Shen, Yichen, et al.
Published: (2026)

Optimal score estimation via empirical Bayes smoothing
by: Wibisono, Andre, et al.
Published: (2024)

Spectral Ranking Inferences based on General Multiway Comparisons
by: Fan, Jianqing, et al.
Published: (2023)

On the Precise Asymptotics of Universal Inference
by: Takatsu, Kenta
Published: (2025)

Statistical Inference under Performativity
by: Li, Xiang, et al.
Published: (2025)

Unified Inference Framework for Single and Multi-Player Performative Prediction: Method and Asymptotic Optimality
by: Zhang, Zhixian, et al.
Published: (2026)

Kernel Ridge Regression Inference
by: Singh, Rahul, et al.
Published: (2023)

Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound
by: Adams, Reuben, et al.
Published: (2022)

A unified recipe for deriving (time-uniform) PAC-Bayes bounds
by: Chugg, Ben, et al.
Published: (2023)