Explore Python Physics Lesson 19 and learn how the Monte Carlo method can approximate Pi with simple yet powerful simulations. In this lesson, we break down the Monte Carlo technique step by step, ...

Abstract: Genetic programming (GP) has achieved promising results without relying on the extraction of prior knowledge, e.g., fixed network architecture. However, most existing GP methods guide the ...

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 ...

This repository contains the JAX implementation that accompanies the paper Probabilistic programming with programmable variational inference, as well as the experiments used to generate figures and ...

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 ...

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 ...