• An Introduction to Modern Statistical Learning
  • Preface
  • 1 Introduction
  • I Representation and Inference
  • II Learning
    • 4 A Mathematical Framework for Learning
    • 5 Learning Discriminative Models
    • 6 Learning Generative Models with Latent Variables
    • 7 Learning Invertible Generative Models
    • 8 Learning Non-Invertible Generative Models
    • 9 Learning with Reparameterizations
    • 10 Learning Energy-Based Models
    • Appendix
    • A Bonus Material
    • B Mathematical Appendix
      • B.1 Matrix Calculus
      • B.2 Probability and Statistics
      • B.3 Matrix Identities
    • C A Review of Probabilistic Graphical Models
    • Bibliography

Mathematical Appendix

Appendix B Mathematical Appendix

  • B.1 Matrix Calculus
  • B.2 Probability and Statistics
  • B.3 Matrix Identities