Extended educational sessions that offer attendees the opportunity to learn research methods and techniques from prominent psychological scientists.

Concr CEO Irina Babina and CTO Matthew Griffiths unpack how Bayesian foundation models can excel at uncertainty management to ...

In the 20th-century statistics wars, Bayesians were underdogs. Now their methods may help speed treatments to market.

Bayesian statistical models use prior data to update the probability of a hypothesis as new evidence emerges. Image credit: PeopleImages / Shutterstock.com Bayesian statistical models could help ...

We discuss Bayesian approaches for learning Bayesian networks from data. First, we review a metric for computing the relative posterior probability of a network structure given data developed by ...

Anonymous social media users can now use large-language models (LLMs) to know the likelihood of someone guessing their identity based on the information they disclose in their posts. That’s because a ...

Bayesian methods have emerged as a robust framework for assessing system reliability in environments marked by uncertainty and limited data availability. By incorporating prior knowledge and updating ...

Bayesian statistics remain popular for addressing inverse problems, whereby quantities of interest are determined from their noisy and indirect observations. Bayes’ theorem forms the foundation of ...

Abstract: In this work, we have developed a variational Bayesian inference theory of elasticity, which is accomplished by using a mixed Variational Bayesian inference Finite Element Method (VBI-FEM) ...

For whom? The events are open to all interested, within or outside of KI. The events are free of charge. The program is tailored towards users of statistics (but you don’t need to be a statistician), ...