Bayes' Theorem: What It Is, Formula, and Examples

Bayes' theorem is a statistical formula used to calculate conditional probability. Learn how it works, how to calculate it ...
AHA/ASA Journals

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
IEEE

Conditional Random Field Features and Structure Assessment for Digital Terrain Modeling

Abstract: The conditional random field is a suitable framework for contextual classification of two-dimensional (images) and three-dimensional (point clouds) data. This framework is based on ...

The Saturday Spread: Reducing Uncertainty in an Uncertain World (AMZN, CHWY, EXPE)

Fundamentally, a truly valuable financial analysis must spark a posterior belief change relative to the prior — and that’s ...
IEEE

Robust Traffic Prediction From Spatial–Temporal Data Based on Conditional Distribution Learning

Abstract: Traffic prediction based on massive speed data collected from traffic sensors plays an important role in traffic management. However, it is still challenging to obtain satisfactory ...
GitHub

Feature Space Singularity for Out-of-Distribution Detection

The central idea of FSSD algorithm is to use the following FSSD score to tell OoD samples from in-distribution ones: where is the feature extractor and is the Feature Space Singularity (FSS). We ...