Bayes' Theorem: What It Is, Formula, and Examples

Bayes' theorem is a statistical formula used to calculate conditional probability. Learn how it works, how to calculate it ...
IEEE

Variational Bayesian inference based 2D-DOAs estimation for time-varying number of dynamic sources

Abstract: This paper proposes a variational Bayesian inference (VBI) based algorithm for gridless and online estimation of multiple two-dimensional directions of arrival (2D-DOAs), whose number and ...
GitHub

bayesian-experimental-design

In this work, we develop a new framework for designing experiments that are robust to model misspecification through generalised Bayesian inference. This repository contains the files needed to ...
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 ...
marktechpost

Meet oLLM: A Lightweight Python Library that brings 100K-Context LLM Inference to 8 GB Consumer GPUs via SSD Offload—No Quantization Required

oLLM is a lightweight Python library built on top of Huggingface Transformers and PyTorch and runs large-context Transformers on NVIDIA GPUs by aggressively offloading weights and KV-cache to fast ...
Frontiers

A leptin-based Bayesian inference of a pro-satiety state reflects a basal circadian rhythm in women with obesity

Department of Biomedical Engineering, Tandon School of Engineering, New York University, New York, NY, United States Introduction: Leptin, primarily secreted by adipose tissue, is a critical hormone ...
IEEE

Variational Bayesian Inference-Inspired Network for Compressive Spectral Imaging

Abstract: In coded aperture snapshot spectral imaging (CASSI) systems, model-based approaches highly rely on the handcrafted priors, while data-driven methods overlook the physical degradation process ...
GitHub

SandyGCabanes/Anonymized-Survey-Data-Modeling-with-Bayesian-Networks-in-Python

Synthetic dataset outputs for public analysis without privacy risk. Part of my current workflow as survey leader of the Data Engineering Pilipinas group. Comparable distributions per column: based on ...
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 ...