Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

Trained on 9.7 trillion tokens of evolutionary data, EDEN designs therapeutics from large gene insertion to antimicrobial peptides.

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

Abstract: In this letter, we propose the B-GHF framework, an end-to-end collision state inference method based on a Bayesian framework that does not rely on external force/torque (F/T) sensors in the ...

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...

Abstract: This article presents a novel deep learning model, the Attentive Bayesian Multi-Stage Forecasting Network (ABMF-Net), designed for robust forecasting of electricity price (USD/MWh) and ...

We use Bayesian meta-analysis methods to estimate the impact of unconditional cash transfers (UCTs). Aggregating evidence from 115 studies of 72 UCT programs in middle and low income countries, we ...

*UPDATE 11/16/23: pip package now available. Use "pip install bnnsurv". Tested with TensorFlow 2.13 and TensorFlow Probability 0.21. See test file for how to use. This repository is the official ...

Incrementality testing in Google Ads is suddenly within reach for far more advertisers than before. Google has lowered the barriers to running these tests, making lift measurement possible even ...

I’m going to go ahead and say it: what happens online doesn’t always necessarily square up with what’s actually going on in real life. Yes, we all know that Elon Musk’s political opinions are ...