PharmExec

Bringing the Bayesian Method to Clinical Trials: Q&A with Dr. Stacy Lindborg

In the announcement, FDA Commissioner Mackary said, “Bayesian methodologies help address two of the biggest problems of drug ...
IEEE

Flow Matching Bayesian Inference for Permeability Field Inversion

We consider stochastic inverse problems with expensive forward models (e.g., PDE/ODE solvers). We propose a transformer-parameterized Conditional Flow Matching (CFM) that learns a time-dependent ...
Scientific Research Publishing

Hill, J.L. (2011) Bayesian Nonparametric Modeling for Causal Inference. Journal of Computational and Graphical Statistics, 20, 217-240.

ABSTRACT: Special education services are designed to provide tailored support for students with diverse learning needs, with the expectation of improving academic achievement. This study examines the ...
GitHub

Does DoWhy support inference and variable manipulation on hybrid network? How to write this simple example

I did not find an example using DoWhy to do inference and variable manipulation on a hybrid network, which has both categorical and continuous variables. I tried the ...
GitHub

psoerensen/bayesian-linear-regression

This repository includes theoretical notes, slides, and hands-on R examples for exploring Bayesian Linear Regression. It introduces both classical and Bayesian regression methods, showing how to ...
Scientific Research Publishing

Hill, J.L. (2011) Bayesian Nonparametric Modeling for Causal Inference.

ABSTRACT: This study investigates the persistent academic impacts of the Head Start program, a federal government-funded early childhood intervention, using data from the Early Childhood Longitudinal ...
Frontiers

A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools

A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...
PNAS

Bayesian phylodynamic inference of population dynamics with dormancy

Dormancy is a widespread bet-hedging strategy across taxa, enabling organisms to survive natural and anthropogenic disturbances. It fundamentally alters eco-evolutionary processes, including ...
C&EN

TargetSeeker-MS: A Bayesian Inference Approach for Drug–Target Discovery Using Protein Fractionation Coupled to Mass Spectrometry

Department of Molecular Medicine, Scripps Research, 10550 N. Torrey Pines Rd., La Jolla, California 92037, United States The Mass Spectrometry Core for Proteomics and Metabolomics, The Salk Institute ...