:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Sonabend, Aaron, Zhang, Jiangshan, Castro, Edgar, Schwartz, Joel, Coull, Brent A., Lu, Junwei
Format:	Preprint
Published:	2024
Subjects:	Methodology
Online Access:	https://arxiv.org/abs/2411.10858
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Collapsible Kernel Machine Regression for Exposomic Analyses
by: McGee, Glen, et al.
Published: (2024)

Measurement Error-Robust Causal Inference via Constructed Instrumental Variables
by: Miles, Caleb H., et al.
Published: (2024)

Bayesian Multiple Index Models for Environmental Mixtures
by: McGee, Glen, et al.
Published: (2021)

Federated Offline Reinforcement Learning
by: Zhou, Doudou, et al.
Published: (2022)

Scalable Gaussian Process Inference with Stan
by: Hoffmann, Till, et al.
Published: (2023)

A varying-coefficient model for characterizing duration-driven heterogeneity in flood-related health impacts
by: Aggarwal, Sarika, et al.
Published: (2026)

A path-specific effect approach to mediation analysis with time-varying mediators and time-to-event outcomes accounting for competing risks
by: Domingo-Relloso, Arce, et al.
Published: (2024)

Bayesian Quantile Estimation and Regression with Martingale Posteriors
by: Fong, Edwin, et al.
Published: (2024)

Estimating Intractable Posterior Distributions through Gaussian Process regression and Metropolis-adjusted Langevin procedure
by: Perrin, Guillaume, et al.
Published: (2025)

Correlated Bayesian Additive Regression Trees with Gaussian Process for Regression Analysis of Dependent Data
by: a, Xuetao Lu, et al.
Published: (2023)

Laplace Approximations for Mixed-Effects and Gaussian Process Quantile Regression
by: Nava, Andrea, et al.
Published: (2026)

Mixture Quantiles Estimated by Constrained Linear Regression
by: Peng, Cheng, et al.
Published: (2023)

Mixture Conditional Regression with Ultrahigh Dimensional Text Data for Estimating Extralegal Factor Effects
by: Shi, Jiaxin, et al.
Published: (2023)

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

Bayesian Bridge Gaussian Process Regression
by: Xu, Minshen, et al.
Published: (2025)

Dirichlet Process-based Robust Clustering using the Median-of-Means Estimator
by: Basu, Supratik, et al.
Published: (2023)

A Random-effects Approach to Regression Involving Many Categorical Predictors and Their Interactions
by: Sun, Hanmei, et al.
Published: (2024)

Bayesian Inference for Stationary Points in Gaussian Process Regression Models for Event-Related Potentials Analysis
by: Yu, Cheng-Han, et al.
Published: (2020)

Scalable Scalar-on-Image Cortical Surface Regression with a Relaxed-Thresholded Gaussian Process Prior
by: Menacher, Anna, et al.
Published: (2024)

Inference of Dependency Knowledge Graph for Electronic Health Records
by: Xu, Zhiwei, et al.
Published: (2023)

Meta-Analysis Without Normality: Estimating the True Effect Distribution with Penalized Gaussian Mixtures
by: Sui, Daihe, et al.
Published: (2026)

Linear Regression: Inference Based on Cluster Estimates
by: Dey, Subhodeep, et al.
Published: (2026)

Latent Factor Point Processes for Patient Representation in Electronic Health Records
by: Knight, Parker, et al.
Published: (2025)

Robust Variable Selection and Estimation Via Adaptive Elastic Net S-Estimators for Linear Regression
by: Kepplinger, David
Published: (2021)

Scalable Expectation Propagation for Mixed-Effects Regression
by: Zhou, Jackson, et al.
Published: (2024)

Dimension Reduction for Large-Scale Federated Data: Statistical Rate and Asymptotic Inference
by: Shen, Shuting, et al.
Published: (2023)

A Gaussian Sliding Windows Regression Model for Hydrological Inference
by: Schrunner, Stefan, et al.
Published: (2023)

EM Approaches to Nonparametric Estimation for Mixture of Linear Regressions
by: Welbaum, Andrew, et al.
Published: (2025)

Evaluating Bias Reduction Methods in Binary Emax Model for Reliable Dose-Response Estimation
by: Zhang, Jiangshan, et al.
Published: (2025)

Energetic Variational Gaussian Process Regression for Computer Experiments
by: Kang, Lulu, et al.
Published: (2023)

Estimating the Effects of Heatwaves on Health: A Causal Inference Framework
by: Grossi, Giulio, et al.
Published: (2025)

Laplace Variational Inference for Dirichlet Process Mixtures of Marked Poisson Point Processes
by: Choi, Minsung, et al.
Published: (2026)

A Random-Effects Approach to Generalized Linear Mixed Model Analysis of Incomplete Longitudinal Data
by: Nguyen, Thuan, et al.
Published: (2024)

Data Sketching and Stacking: A Confluence of Two Strategies for Predictive Inference in Gaussian Process Regressions with High-Dimensional Features
by: Gailliot, Samuel, et al.
Published: (2024)

Comparison of methods for analyzing environmental mixtures effects on survival outcomes and application to a population-based cohort study
by: Mayer, Melanie N., et al.
Published: (2023)

Posterior Projection for Inference in Constrained Spaces
by: Astfalck, Lachlan, et al.
Published: (2018)

Bayesian Additive Regression Tree Copula Processes for Scalable Distributional Prediction
by: Wenkel, Jan Martin, et al.
Published: (2026)

A nutritionally informed model for Bayesian variable selection with metabolite response variables
by: Clark-Boucher, Dylan, et al.
Published: (2025)

Gaussian Transforms Modeling and the Estimation of Distributional Regression Functions
by: Spady, Richard, et al.
Published: (2020)

The Poisson-Gaussian Mixture Process: A Flexible and Robust Approach for Non-Gaussian Geostatistical Modeling
by: Gonçalves, F. B., et al.
Published: (2022)