Saved in:
| Main Authors: | Thanasutives, Pongpisit, Fukui, Ken-ichi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.16881 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptation of uncertainty-penalized Bayesian information criterion for parametric partial differential equation discovery
by: Thanasutives, Pongpisit, et al.
Published: (2024)
by: Thanasutives, Pongpisit, et al.
Published: (2024)
Adaptive Uncertainty-Guided Model Selection for Data-Driven PDE Discovery
by: Thanasutives, Pongpisit, et al.
Published: (2023)
by: Thanasutives, Pongpisit, et al.
Published: (2023)
Data-driven sparse identification of governing PDEs via knockoff filters and multi-criteria trade-offs
by: Thanasutives, Pongpisit, et al.
Published: (2026)
by: Thanasutives, Pongpisit, et al.
Published: (2026)
Variational bagging: a robust approach for Bayesian uncertainty quantification
by: Fan, Shitao, et al.
Published: (2025)
by: Fan, Shitao, et al.
Published: (2025)
Algebraic Geometrical Analysis of Metropolis Algorithm When Parameters Are Non-identifiable
by: Nagata, Kenji, et al.
Published: (2024)
by: Nagata, Kenji, et al.
Published: (2024)
Information Geometry of Wasserstein Statistics on Shapes and Affine Deformations
by: Amari, Shun-ichi, et al.
Published: (2023)
by: Amari, Shun-ichi, et al.
Published: (2023)
Point processes with event time uncertainty
by: Cheng, Xiuyuan, et al.
Published: (2024)
by: Cheng, Xiuyuan, et al.
Published: (2024)
Incorporating structural uncertainty in causal decision making
by: Kaptein, Maurits
Published: (2025)
by: Kaptein, Maurits
Published: (2025)
A review of predictive uncertainty estimation with machine learning
by: Tyralis, Hristos, et al.
Published: (2022)
by: Tyralis, Hristos, et al.
Published: (2022)
Score-based generative models are provably robust: an uncertainty quantification perspective
by: Mimikos-Stamatopoulos, Nikiforos, et al.
Published: (2024)
by: Mimikos-Stamatopoulos, Nikiforos, et al.
Published: (2024)
Corrected generalized cross-validation for finite ensembles of penalized estimators
by: Bellec, Pierre C., et al.
Published: (2023)
by: Bellec, Pierre C., et al.
Published: (2023)
Deep Bayesian Inversion
by: Adler, Jonas, et al.
Published: (2018)
by: Adler, Jonas, et al.
Published: (2018)
Physics-informed kernel learning
by: Doumèche, Nathan, et al.
Published: (2024)
by: Doumèche, Nathan, et al.
Published: (2024)
The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks
by: Bieringer, Sebastian, et al.
Published: (2023)
by: Bieringer, Sebastian, et al.
Published: (2023)
Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning
by: Elliott, Chris, et al.
Published: (2026)
by: Elliott, Chris, et al.
Published: (2026)
Sequential Bayesian Neural Subnetwork Ensembles
by: Jantre, Sanket, et al.
Published: (2022)
by: Jantre, Sanket, et al.
Published: (2022)
Singular Fluctuation as Specific Heat in Bayesian Learning
by: Plummer, Sean
Published: (2025)
by: Plummer, Sean
Published: (2025)
Thermodynamic Response Functions in Singular Bayesian Models
by: Plummer, Sean
Published: (2026)
by: Plummer, Sean
Published: (2026)
Frequentist Guarantees of Distributed (Non)-Bayesian Inference
by: Wu, Bohan, et al.
Published: (2023)
by: Wu, Bohan, et al.
Published: (2023)
Misclassification bounds for PAC-Bayesian sparse deep learning
by: Mai, The Tien
Published: (2024)
by: Mai, The Tien
Published: (2024)
Can Bayesian Neural Networks Make Confident Predictions?
by: Fisher, Katharine, et al.
Published: (2025)
by: Fisher, Katharine, et al.
Published: (2025)
An Equivalence between Bayesian Priors and Penalties in Variational Inference
by: Wolinski, Pierre, et al.
Published: (2020)
by: Wolinski, Pierre, et al.
Published: (2020)
Generalized Bayesian Additive Regression Trees: Theory and Software
by: Saha, Enakshi
Published: (2023)
by: Saha, Enakshi
Published: (2023)
Streaming data recovery via Bayesian tensor train decomposition
by: Huang, Yunyu, et al.
Published: (2023)
by: Huang, Yunyu, et al.
Published: (2023)
Generalized Power Priors for Improved Bayesian Inference with Historical Data
by: Kimura, Masanari, et al.
Published: (2025)
by: Kimura, Masanari, et al.
Published: (2025)
On Reconstructing Training Data From Bayesian Posteriors and Trained Models
by: Wynne, George
Published: (2025)
by: Wynne, George
Published: (2025)
Bayesian Cramér-Rao Bound Estimation with Score-Based Models
by: Crafts, Evan Scope, et al.
Published: (2023)
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)
by: Alberola-Boloix, Enric, et al.
Published: (2026)
Generalising realisability in statistical learning theory under epistemic uncertainty
by: Cuzzolin, Fabio
Published: (2024)
by: Cuzzolin, Fabio
Published: (2024)
Selecting informative conformal prediction sets with false coverage rate control
by: Gazin, Ulysse, et al.
Published: (2024)
by: Gazin, Ulysse, et al.
Published: (2024)
Are Bayesian networks typically faithful?
by: Boeken, Philip, et al.
Published: (2024)
by: Boeken, Philip, et al.
Published: (2024)
Joint learning of a network of linear dynamical systems via total variation penalization
by: Donnat, Claire, et al.
Published: (2025)
by: Donnat, Claire, et al.
Published: (2025)
Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference
by: Kungurtsev, Vyacheslav, et al.
Published: (2024)
by: Kungurtsev, Vyacheslav, et al.
Published: (2024)
A sparse PAC-Bayesian approach for high-dimensional quantile prediction
by: Mai, The Tien
Published: (2024)
by: Mai, The Tien
Published: (2024)
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization
by: Hu, Shouri, et al.
Published: (2022)
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)
by: Khribch, EL Mahdi, et al.
Published: (2026)
Bayes optimal learning in high-dimensional linear regression with network side information
by: Nandy, Sagnik, et al.
Published: (2023)
by: Nandy, Sagnik, et al.
Published: (2023)
Sample efficient inductive matrix completion with noise and inexact side information
by: Yang, Yuepeng, et al.
Published: (2026)
by: Yang, Yuepeng, et al.
Published: (2026)
Bayesian Mixture-of-Experts: Towards Making LLMs Know What They Don't Know
by: Li, Albus Yizhuo
Published: (2025)
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)
by: Adcock, Ben, et al.
Published: (2025)
Similar Items
-
Adaptation of uncertainty-penalized Bayesian information criterion for parametric partial differential equation discovery
by: Thanasutives, Pongpisit, et al.
Published: (2024) -
Adaptive Uncertainty-Guided Model Selection for Data-Driven PDE Discovery
by: Thanasutives, Pongpisit, et al.
Published: (2023) -
Data-driven sparse identification of governing PDEs via knockoff filters and multi-criteria trade-offs
by: Thanasutives, Pongpisit, et al.
Published: (2026) -
Variational bagging: a robust approach for Bayesian uncertainty quantification
by: Fan, Shitao, et al.
Published: (2025) -
Algebraic Geometrical Analysis of Metropolis Algorithm When Parameters Are Non-identifiable
by: Nagata, Kenji, et al.
Published: (2024)