Skip to content

machine-learning-2020

  • Home
  • ML-101
  • ML-102
  • Books
  • Learning
    • DataBase
    • Tutorial
    • Lectures
    • Videos
    • Computer Experiments
    • References
    • PhD Thesis
      • English
      • French
  • Applications
    • TCAD-EDA
    • Semiconductor
    • Software
      • SCIKITLEARN
      • Sandia National Laboratories
        • DAKOTA
        • Publications
  • Machine Learning Techniques
    • General Papers
    • Gaussian Process
      • Gaussian Process : PhD Thesis
      • Publications
    • Artificial Neural Networks
    • Genetic Algorithm
    • Meta-Models
    • Genetic Programming
    • Least Squares, Weighted Least Squares, Moving Least Squares Methods

Keith Dalbey

  • Video : UQ12 – MS1-3 Effective and Efficient Handling of Ill-Conditioned Correlation Matrices in Kriging and Gradient Enhanced Kriging Emulators through Pivoted Cholesky Factorization
  • Effective & Efficient Handling of Ill – Conditioned Correlation Matrices in Kriging & Gradient Enhanced Kriging Emulators Through Pivoted Cholesky Factorization
  • Efficient and Robust Gradient Enhanced Kriging Emulators
  • Using Statistical and Computer Models to Quantify Volcanic Hazards
  • K-d darts: Sampling by k-dimensional flat searches
  • Fast Generation of Space-filling Latin Hypercube Sample Designs
  • Progress Towards Nested Space and Sub-Space Filling Latin Hypercube Sample Designs
Post navigation
Journals
Gaussian Process : Papers
© 2026 machine-learning-2020 • Built with GeneratePress