Empirical Inference Department

The problems studied in the department can be subsumed under the heading of empirical inference. This term refers to inference performed on the basis of empirical data.

The type of inference can vary, including for instance inductive learning (estimation of models such as functional dependencies that generalize to novel data sampled from the same underlying distribution), or the inference of causal structures from statistical data (leading to models that provide insight into the underlying mechanisms, and make predictions about the effect of interventions). Likewise, the type of empirical data can vary, ranging from sparse experimental measurements (e. g., microarray data) to visual patterns. Our department is conducting theoretical, algorithmic, and experimental studies to try and understand the problem of empirical inference.

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