| layout | title | description |
|---|---|---|
default |
Information Geometry |
A summary of information geometry. |
Information geometry studies the geometry of spaces of probability distributions, with particular focus to topics related to:
- the Fisher information metric (a Riemannian metric),
- the dually flat structure on these spaces,
- divergences between probability distributions,
- etc.
- Amari, Nagoka --- Methods of Information Geometry (classic reference; best choice for a first reading; explains most of the basic ideas and the geometry needed; great focus on the dual connections)
- Calin, Udrişte --- Geometric Modeling in Probability and Statistics (connects to information theory; full of examples; is divided in two parts: one about statistical models, and the other about abstract statistical manifolds)
- Ay, Jost, Lê, Schwachhöfer --- Information Geometry (modern reference; definetely the most most geometric abstract one; shows many possible generalizations)
- Amari --- Information Geometry and Its Applications (provides a overview of many applications of information geometry to different fields)
- Nielsen --- The Many Faces of Information Geometry (a good quick overview of the area)
- Information Geometry (Springer)
- Entropy (MDPI)