Garage door openers: Don’t leave home without one. Unless, of course, you don’t have a garage. These remotes can be used again and again and reprogrammed as often as you need. You can also buy ...

Probabilistic programming is an approach to computing based on the idea that probabilistic models can be naturally and efficiently represented as executable code. This idea has enabled researchers to ...

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 ...

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 ...

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 ...

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 ...