Nature

A Bayesian perspective on observers’ inference of group norms

Inferring group norms is crucial for adapting behaviors in novel situations, but its underlying basis and computational account remain unclear. This study manipulated the prevalence of norm-consistent ...
Nature

High-throughput parameter estimation from experimental data using Bayesian Inference with accelerated sampling

BIAS (Bayesian Inference with Accelerated Sampling) is a high-throughput parameter estimation framework designed to rapidly infer the root causes of device underperformance in real time. It integrates ...
Phys.org

Researchers develop Bayesian inference for hidden dependence structures in multi-group high-dimensional data

In today's scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly increasing ...
Diginomica

Can Bayesian Networks provide answers when Machine Learning comes up short? It's a question of probabilities

Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here's a deeper look at why "Bayes Nets" are underrated - especially when it comes to addressing probability and ...