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 ...

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 ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

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 ...

ABSTRACT: The most commonly used strategy of the speculative investments in options is a statistical arbitrage between the objective underlying price distribution which the price is following and the ...

Learning to program in C on an online platform can provide structured learning and a certification to show along with your resume. Looking into learning C, one of the most popular programming ...

Generative models of tabular data are key in Bayesian analysis, probabilistic machine learning, and fields like econometrics, healthcare, and systems biology. Researchers have developed methods to ...