This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models (LMM). It ...
What’s often misunderstood about Google’s incrementality testing and how Bayesian models use probability to guide better ...
The Temporal Fusion Transformer model provides near-real-time insights into sintering temperatures, addressing critical ...
A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to estimate AGB of individual trees in natural secondary forests of northeastern ...
An analysis by Shinshu University and the Distribution Economics Institute of Japan shows that wholesale prices for ...
By a News Reporter-Staff News Editor at Disease Prevention Daily-- A new study on Drugs and Therapies- Kinase Inhibitors is now available. Financial supporters for this research include Taiju Life ...
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This one change made my Home Assistant automations far more accurate
The beauty of Bayesian sensors is that they can make your Home Assistant automations much more accurate. If your cat does ...
The Virtual Brain Inference (VBI) toolkit enables efficient, accurate, and scalable Bayesian inference over whole-brain network models, improving parameter estimation, uncertainty quantification, and ...
There are already tens of thousands of pieces of large debris in orbit, some of which pose a threat to functional satellites. Various agencies and organizations have been developing novel solutions to ...
Abstract: This letter proposes a Bayesian channel estimation method that leverages on the a priori information provided by the Electromagnetic Digital Twin’s (EM-DT) representation of the environment.
Released MoGe-2, a state-of-the-art model for monocular geometry, with these new capabilities in one unified model: Note: MoGe should be compatible with most ...
Abstract: This paper presents a Bayesian data fusion framework for estimating journey time variability that uses a mixture distribution model to classify feeding data into different traffic states.
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