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 ...

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 ...

Receive the the latest news, research, and presentations from major meetings right to your inbox. TCTMD ® is produced by the Cardiovascular Research Foundation ® (CRF). CRF ® is committed to igniting ...

This study explores the efficacy of Bayesian estimation in modeling the orientation and direction selectivity of neurons in the primary visual cortex (V1). Unlike traditional methods such as least ...

This study examines how trade shocks that start in one large economy ripple through other countries and how long those effects stick around. Using quarterly bilateral-trade data for 2012-2023, the ...

Mathematics Department, Egerton University, Njoro Nakuru, Kenya. Bayesian techniques have been applied in many epidemiological settings, such as disease monitoring, outbreak simulation, and prevalence ...

The mathematics that enable sensor fusion include probabilistic modeling and statistical estimation using Bayesian inference and techniques like particle filters, Kalman filters, and α-β-γ filters, ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Sediment plumes created by dredging or mining activities have an impact on the ecosystem in a much larger area than the mining or dredging area itself. It is therefore important and sometimes ...