What do a 20th-century physicist, an 18th-century statistician and an ancient Greek philosopher have in common? They all knew how to extrapolate with incredible accuracy. Columnist Jacob Aron explains ...

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable Bayesian inference in deep learning models to quantify principled uncertainty estimates in ...

The FDA has released draft guidance on how sponsors can use Bayesian models for clinical trials.

Marty Makary was appointed commissioner of the Food and Drug Administration (FDA) in 2025. The prominent surgeon, medical researcher, bestselling author, and critic of the medical ...

This repository contains the main codebase for the undergraduate thesis: "Fusión de sensores para el seguimiento de trayectorias en vehículos autónomos mediante modelos probabilísticos" (Sensor Fusion ...

Determining the causal effect of special education is a critical topic when making educational policy that focuses on student achievement. However, current special education research is facing ...

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Heterogeneity among experimental units can introduce experimental errors, necessitating the use of techniques that enhance statistical inferences to address this issue. One effective approach is ...

Abstract: This work studies an information-theoretic performance limit of an integrated sensing and communication (ISAC) system where the goal of sensing is to ...

ABSTRACT: In statistical decision theory, the risk function quantifies the average performance of a decision over the sample space. The risk function, which depends on the parameter of the model, is ...