ABSTRACT: This paper introduces a methodology that enables the relational learning framework to incorporate quantitative data derived from experimental studies in microbial ecology. The focus of using ...

Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

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 ...

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 ...

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 ...

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 ...

Website of the PhD course on Foundations of Probabilistic Programming at IT University of Copenhagen, Spring 2023. The course is organized as a reading group. Each week we discuss different topics and ...

Data-driven approaches are becoming increasingly common as problem-solving tools in many areas of science and technology. In most cases, machine learning models are the key component of these ...

Meta AI releases the beta version of Bean Machine, a probabilistic programming framework based on PyTorch that makes it simple to describe and learn about uncertainty in machine learning models used ...