One of the most hilarious things you can do with an LLM-based chatbot is to ask it to do calculations. If it’s a well-written ...

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 ...

Abstract: In this work, we have developed a variational Bayesian inference theory of elasticity, which is accomplished by using a mixed Variational Bayesian inference Finite Element Method (VBI-FEM) ...

Variational inference is a family of optimisation-based methods for approximating complex posterior distributions in Bayesian models. By transforming inference into an optimisation problem, these ...

PyVBMC is a Python implementation of the Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference, previously implemented in MATLAB. VBMC is an approximate inference method ...

A significant shift is under way in artificial intelligence, and it has huge implications for technology companies big and small. For the past half-decade, most of the focus in AI has been on training ...

Animals survive in changing and unpredictable environments by not merely responding to new circumstances, but also, like humans, by forming inferences about their surroundings—for instance, squirrels ...

They say the holidays are the most wonderful time of the year, but around these parts, we know nothing tops the launch of the annual Popsugar Reading Challenge — our take on a virtual book club that ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When OpenAI’s ChatGPT first exploded onto the scene in late 2022, it sparked a global obsession ...

Its deal with Merck & Co. is the latest in a series of Variational AI collaborations. (iStock/Getty Images Plus) Merck & Co. has doubled down on its partnership with Variational AI, striking a deal ...