:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Tang, Bingjing, Palacios, Julia
Format:	Preprint
Published:	2024
Subjects:	Methodology Computation Machine Learning
Online Access:	https://arxiv.org/abs/2406.19722
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generative Bayesian Computation as a Scalable Alternative to Gaussian Process Surrogates
by: Polson, Nick, et al.
Published: (2026)

Scalable Bayesian Structure Learning for Gaussian Graphical Models Using Marginal Pseudo-likelihood
by: Mohammadi, Reza, et al.
Published: (2023)

Gaussian Process Boosting
by: Sigrist, Fabio
Published: (2020)

Bayesian Nonlinear PDE Inference via Gaussian Process Collocation with Application to the Richards Equation
by: Yang, Yumo, et al.
Published: (2025)

Bayesian Causal Inference with Gaussian Process Networks
by: Giudice, Enrico, et al.
Published: (2024)

A Bayesian Take on Gaussian Process Networks
by: Giudice, Enrico, et al.
Published: (2023)

Structured Learning in Time-dependent Cox Models
by: Wang, Guanbo, et al.
Published: (2023)

Robust and Conjugate Spatio-Temporal Gaussian Processes
by: Laplante, William, et al.
Published: (2025)

Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
by: Petit, Sébastien, et al.
Published: (2022)

Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimization
by: Pion, Aurélien, et al.
Published: (2026)

Predicting Electricity Consumption with Random Walks on Gaussian Processes
by: Hashimoto-Cullen, Chloé, et al.
Published: (2024)

Statistical inference after variable selection in Cox models: A simulation study
by: Schemet, Lena, et al.
Published: (2026)

Summarizing Bayesian Nonparametric Mixture Posterior -- Sliced Optimal Transport Metrics for Gaussian Mixtures
by: Nguyen, Khai, et al.
Published: (2024)

Amortized Bayesian Local Interpolation NetworK: Fast covariance parameter estimation for Gaussian Processes
by: Feng, Brandon R., et al.
Published: (2024)

Bayesian Cox model with graph-structured variable selection priors for multi-omics biomarker identification
by: Hermansen, Tobias Østmo, et al.
Published: (2025)

Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature
by: Li, Chengkun, et al.
Published: (2023)

Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures
by: Thai, Tuan, et al.
Published: (2025)

Modular Jump Gaussian Processes
by: Flowers, Anna R., et al.
Published: (2025)

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

Exact and Approximate MCMC for Doubly-intractable Probabilistic Graphical Models Leveraging the Underlying Independence Model
by: Chen, Yujie, et al.
Published: (2025)

Machine Learning Assisted Adjustment Boosts Efficiency of Exact Inference in Randomized Controlled Trials
by: Yu, Han, et al.
Published: (2024)

Scalable Monte Carlo for Bayesian Learning
by: Fearnhead, Paul, et al.
Published: (2024)

Temperature Optimization for Bayesian Deep Learning
by: Ng, Kenyon, et al.
Published: (2024)

Bayesian Federated Inference for Survival Models
by: Pazira, Hassan, et al.
Published: (2024)

Generative Bayesian Filtering and Parameter Learning
by: Marcelli, Edoardo, et al.
Published: (2025)

Variational Inference for Bayesian MIDAS Regression
by: Simeone, Luigi
Published: (2026)

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

Conditioning Gaussian Processes on Almost Anything
by: Moss, Henry, et al.
Published: (2026)

Self-Supervised Learning with Gaussian Processes
by: Duan, Yunshan, et al.
Published: (2025)

Adaptive Gaussian Process Search for Simulation-Based Sample Size Estimation in Clinical Prediction Models: Validation of the pmsims R Package
by: Olaniran, Oyebayo Ridwan, et al.
Published: (2026)

Bayesian Multiple Multivariate Density-Density Regression
by: Nguyen, Khai, et al.
Published: (2026)

LITE: Efficiently Estimating Gaussian Probability of Maximality
by: Menet, Nicolas, et al.
Published: (2025)

Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?
by: Kim, Hwanwoo, et al.
Published: (2025)

Approximate Bayesian inference for cumulative probit regression models
by: Aliverti, Emanuele
Published: (2025)

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

New Bounds for Sparse Variational Gaussian Processes
by: Titsias, Michalis K.
Published: (2025)

PASOA- PArticle baSed Bayesian Optimal Adaptive design
by: Iollo, Jacopo, et al.
Published: (2024)

bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond)
by: Umlauf, Nikolaus, et al.
Published: (2019)

Bayesian Ensembling: Insights from Online Optimization and Empirical Bayes
by: Waxman, Daniel, et al.
Published: (2025)

H-AddiVortes: Heteroscedastic (Bayesian) Additive Voronoi Tessellations
by: Stone, Adam J., et al.
Published: (2025)