- معلم: Tanveer Hannan
- معلم: Andrea Maldonado Hernandez
- معلم: Gabriel Marques Tavares
- معلم: Thomas Seidl
- معلم: Sandra Gilhuber
- معلم: Zongyue Li
- معلم: Matthias Schubert
- معلم: Niklas Strauß
- معلم: Sandra Gilhuber
- معلم: Matthias Schubert
- معلم: Thomas Seidl
- معلم: Göran Kauermann
- معلم: Victor Tuekam Mambou
Login: Please contact Susanne Dandl
Target group: Master Data Science
Course Description:
For decades, research in machine learning and causality progressed independently of each other. This seminar sheds light on the recent advances on the intersection between the two, which can be classified into two primary areas:
(1) How can machine learning algorithms contribute to causality? Examples are the estimation of heterogeneous treatment effects and causal structure learning.
(2) How can causal knowledge enhance machine learning models, for example, w.r.t. their generalizability, interpretability, and fairness?
- معلم: Ludwig Bothmann
- معلم: Susanne Dandl
Schedule
- Class: Tuesday, 12 - 14 c.t.
Enrollment key
- This class is only for students enrolled in the elite master program Data Science. You should have received the enrollment key via e-mail.
- If not, please let me know via e-mail giuseppe.casalicchio[at]stat.uni-muenchen.de to ask for the enrollment key.
- معلم: Giuseppe Casalicchio