Santo Thies, M.Sc.
Research Assistant
Chair of Artificial Intelligence and Machine Learning
Office address:
Akademiestraße 7
Room 113
80799 Munich
My current research focuses on approximations and application of game theoretic concepts such as the shapley value and shapley interactions to the current field of explainable artificial intelligence. I work on developing new approximation algorithms for shapley interactions, which are both scalable to large feature counts and efficient. Particularly consistent estimator are of main interest.
Further I am also interested in preference learning and its connections to game theory.