Hamiltonian Monte Carlo Methods in Machine Learning

ISBN-13: 9780443190353 / Angielski / Miękka / 2023 / 300 str.

Sout University of Johannesburg Wilson Tsakane (Researcher

Spis treści

1. Introduction to Hamiltonian Monte Carlo 2. Sampling Benchmarks and Performance Metrics 3. Stochastic Volatility Metropolis-Hastings 4. Quantum-Inspired Magnetic Hamiltonian Monte Carlo 5. Generalised Magnetic and Shadow Hamiltonian Monte Carlo 6. Shadow Hamiltonian Monte Carlo Methods 7. Adaptive Shadow Hamiltonian Monte Carlo Methods 8. Adaptive Noncanonical Hamiltonian Monte Carlo 9. Antithetic Hamiltonian Monte Carlo Techniques 10. Application: Bayesian Neural Network Inference in Wind Speed Forecasting 11. Application: A Bayesian Analysis of Lockdown Alert Level Framework for Combating COVID-19 12. Application: Probabilistic Inference of Equity Option Prices Under Jump-Di 13. Application: Bayesian Inference of Local Government Audit Outcomes 14. Open Problems in Sampling

Appendix A: Separable Shadow Hamiltonian B: Automatic Relevance Determination C: Audit Outcome Literature Survey