Cover Image

Singular Fluctuation as Specific Heat in Bayesian Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Plummer, Sean
Format:	Preprint
Published:	2025
Subjects:	Statistics Theory Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Thermodynamic Response Functions in Singular Bayesian Models
by: Plummer, Sean
Published: (2026)

Observable Geometry of Singular Statistical Models
by: Plummer, Sean
Published: (2026)

Hypothesis Testing over Observable Regimes in Singular Models
by: Plummer, Sean
Published: (2026)

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

Linear Response Estimators for Singular Statistical Models
by: Elliott, Chris, et al.
Published: (2026)

Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning
by: Elliott, Chris, et al.
Published: (2026)

From Tail Universality to Bernstein-von Mises: A Unified Statistical Theory of Semi-Implicit Variational Inference
by: Plummer, Sean
Published: (2025)

Learning Dynamic Bayesian Networks from Data: Foundations, First Principles and Numerical Comparisons
by: Kungurtsev, Vyacheslav, et al.
Published: (2024)

Leave-one-out Singular Subspace Perturbation Analysis for Spectral Clustering
by: Zhang, Anderson Y., et al.
Published: (2022)

Deep Bayesian Inversion
by: Adler, Jonas, et al.
Published: (2018)

General Bayesian Policy Learning
by: Kato, Masahiro
Published: (2026)

Sequential Bayesian Neural Subnetwork Ensembles
by: Jantre, Sanket, et al.
Published: (2022)

On uncertainty-penalized Bayesian information criterion
by: Thanasutives, Pongpisit, et al.
Published: (2024)

Optimal Estimation of Shared Singular Subspaces across Multiple Noisy Matrices
by: Ma, Zhengchi, et al.
Published: (2024)

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

Optimal Sparse Singular Value Decomposition for High-dimensional High-order Data
by: Zhang, Anru, et al.
Published: (2018)

Proximal Path-Specific Inference
by: Bai, Yang, et al.
Published: (2026)

Singular leaning coefficients and efficiency in learning theory
by: Aoyagi, Miki
Published: (2025)

Can Bayesian Neural Networks Make Confident Predictions?
by: Fisher, Katharine, et al.
Published: (2025)

Misclassification bounds for PAC-Bayesian sparse deep learning
by: Mai, The Tien
Published: (2024)

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

Generalized Bayesian Additive Regression Trees: Theory and Software
by: Saha, Enakshi
Published: (2023)

Bayesian Design Principles for Frequentist Sequential Learning
by: Xu, Yunbei, et al.
Published: (2023)

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

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

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

Streaming data recovery via Bayesian tensor train decomposition
by: Huang, Yunyu, et al.
Published: (2023)

Bayesian Cramér-Rao Bound Estimation with Score-Based Models
by: Crafts, Evan Scope, et al.
Published: (2023)

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

Hierarchical Bayesian Operator-induced Symbolic Regression Trees for Structural Learning of Scientific Expressions
by: Roy, Somjit, et al.
Published: (2025)

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

A sparse PAC-Bayesian approach for high-dimensional quantile prediction
by: Mai, The Tien
Published: (2024)

Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization
by: Hu, Shouri, et al.
Published: (2022)

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

Context-Specific Causal Graph Discovery with Unobserved Contexts: Non-Stationarity, Regimes and Spatio-Temporal Patterns
by: Rabel, Martin, et al.
Published: (2025)

Bayesian Mixture-of-Experts: Towards Making LLMs Know What They Don't Know
by: Li, Albus Yizhuo
Published: (2025)

How many measurements are enough? Bayesian recovery in inverse problems with general distributions
by: Adcock, Ben, et al.
Published: (2025)

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

Are Bayesian networks typically faithful?
by: Boeken, Philip, et al.
Published: (2024)

PAC-Bayesian risk bounds for fully connected deep neural network with Gaussian priors
by: Mai, The Tien
Published: (2025)