Gut bacteria play a major role in human health, influencing everything from digestion to immunity and mood. Yet the scale and complexity of data relating to the microbiome and a series of complex ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Andy Brinkmeyer shares how engineering ...

We introduce a methodology for coding Bayesian statistical models in Python with JAX that follows the design pattern of the Stan probabilistic programming language. This allows a direct, line-by-line ...

Scientists have turned to advanced AI to decode the intricate ecosystem of gut bacteria and their chemical signals. Using a Bayesian neural network called VBayesMM, researchers can now identify ...

Abstract: This article introduces the Bayesian probabilistic fuzzy neural network (BPFNN), a unified architecture designed to overcome the challenges of conventional fuzzy clustering and neural ...

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...

Abstract: Bayesian Neural Networks (BNNs) offer robust uncertainty estimation capabilities through probabilistic modeling, yet their prohibitively high computational complexity and resource ...

Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body's chemistry and each ...

Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body’s chemistry and each ...

If you have a health insurance plan, you’ve probably come across the terms “in-network” and “out-of-network.” Simply put, in-network means the doctors or hospitals you visit contract with your ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...