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 ...

The Nature Index 2024 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

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 ...

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, ...

Ask the publishers to restore access to 500,000+ books. A line drawing of the Internet Archive headquarters building façade. An illustration of a heart shape "Donate to the archive" An illustration of ...

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 ...

Microseismic (MS) source location is an integral component of MS technology and essential to understanding the rock failure mechanism and avoiding potential geological hazards in underground rock ...

Abstract: Probabilistic programming languages rely fundamentally on some notion of sampling, and this is doubly true for probabilistic programming languages which perform Bayesian inference using ...

Awesome-spatial-temporal-scientific-machine-learning-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about ...