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 ...

Ada, a programming language born in the late 70s, has managed to break into the top 10 of the TIOBE Index for July 2025. The sudden return of this old-timer has developers debating whether it’s a ...

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 ...

Functional programming, as the name implies, is about functions. While functions are part of just about every programming paradigm, including JavaScript, a functional programmer has unique ...

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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 ...