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; great choice for a first reading; explains most of the basic ideas and the geometry needed; much 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; explains geometric abstractions; 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)