The tutorial will be held on .Top
In the field of causality we are interested in answering questions like how a system reacts under interventions (e.g. in gene knock-out experiments). These questions go beyond statistical dependencies and can therefore not be answered by standard regression or classification techniques. While humans are very efficient in learning causal relations between few random variables, we require automated procedures in situations where many and/or high-dimensional data are available.
In this tutorial you will learn about the interesting problem of causal inference and recent developments in the field. The tutorial does not require any prior knowledge about causality.
Jonas Peters from Max Planck Institute for Intelligent SystemsTop