The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

Fatigue life analysis and probabilistic modeling constitute a pivotal area in materials science and engineering, addressing the prediction of material degradation and failure under cyclic loading ...

The main focus of this short course will be the Bayesian aspect of it. That means this is a slightly more advanced course requiring some knowledge of basic probability, regression methods, and the R ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the naive Bayes regression technique, where the goal is to predict a single numeric value. Compared to other ...

What Is A Probabilistic Model? A probabilistic model is a statistical tool that accounts for randomness or uncertainty when predicting future events. Instead of giving a definitive answer, it ...

A US-Dutch research team has developed a novel bidding strategy for PV plant operators participating in electricity spot markets. It is based on turning probabilistic solar power forecasts into ...

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those ...

This course is available on the MSc in Applied Social Data Science, MSc in Data Science, MSc in Econometrics and Mathematical Economics, MSc in Health Data Science, MSc in Operations Research & ...