The Oklahoma Court of Criminal Appeals has unanimously affirmed the use of BulletProof, a probabilistic genotyping software program, in the assault and battery trial of Patrick Marquise Napoleon, who ...

Probabilistic Programming is a way of defining probabilistic models by overloading the operations in standard programming language to have probabilistic meanings. The goal is to specify probabilistic ...

Distributed Entropy-Weighted Probabilistic Programming for Real-Time Crisis Zone Epidemiological Modeling Note: This README is an ultra-condensed summary of the research reports published by ...

Abstract: Causal inference is an important field in data science and cognitive artificial intelligence. It requires the construction of complex probabilistic models to describe the causal ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Satellite data provides essential insights into the spatiotemporal distribution of CO ...

ABSTRACT: Statistical biases may be introduced by imprecisely quantifying background radiation reference levels. It is, therefore, imperative to devise a simple, adaptable approach for precisely ...

This tutorial will introduce a new paradigm for agent-based models (ABMs) that leverages automatic differentiation (AD) to efficiently compute simulator gradients. In particular, this tutorial will ...

In the lead up to this year’s presidential election, Andrew Gelman, a professor of political science and statistics, collaborated with Ben Goodrich, an instructor in the political science department, ...

Researchers have developed an easy-to-use tool that enables someone to perform complicated statistical analyses on tabular data using just a few keystrokes. Their method combines probabilistic AI ...

A new tool makes it easier for database users to perform complicated statistical analyses of tabular data without the need to know what is going on behind the scenes. GenSQL, a generative AI system ...