qualitysafety.bmj

Grand rounds in methodology: four critical decision points in statistical process control evaluations of quality improvement initiatives

Quality improvement (QI) projects often employ statistical process control (SPC) charts to monitor process or outcome measures as part of ongoing feedback, to inform successive Plan-Do-Study-Act ...
Visual Studio Magazine

Neural Network Regression from Scratch Using C#

Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction model, says Dr. James McCaffrey of Microsoft Research in presenting this ...
IEEE

An Intuitive Tutorial to Gaussian Process Regression

Abstract: This tutorial aims to provide an intuitive introduction to Gaussian process regression (GPR). GPR models have been widely used in machine learning applications due to their representation ...
Visual Studio Magazine

Gaussian Process Regression from Scratch Using C#

GPR works well with small datasets and generates a metric of confidence of a predicted result, but it's moderately complex and the results are not easily interpretable, says Dr. James McCaffrey of ...
Frontiers

Sparse Gaussian Process Regression for Landslide Displacement Time-Series Forecasting

Landslide hazards are complex nonlinear systems with a highly dynamic nature. Accurate forecasting of landslide displacement and evolution is crucial for the prevention and mitigation of landslide ...
Scientific Research Publishing

Path Loss Modeling: A Machine Learning Based Approach Using Support Vector Regression and Radial Basis Function Models ()

1 College of Engineering, Anderson University, Anderson, SC, USA. 2 Department of Management Information Systems, Girne American University, Girne, Cyprus. 3 Computer Science Department, Florida A&M ...
GitHub

davitpapikyan/Gaussian-Processes-for-Machine-Learning

The repository includes the presentation, paper and jupyter notebook covering the topic "Gaussian Processes for Regression" at Technical University of Munich within the scope of seminar "Gaussian ...