We develop new methods and algorithms for coping with uncertainty in artificial intelligence, focusing in particular on approximate Bayesian inference of probabilistic programs. We also solve ...

Integrated Inferences develops a framework for using causal models and Bayesian updating for qualitative and mixed-methods research. By making, updating, and querying causal models, researchers are ...

Bayesianism is enjoying a revival across many fields, and it offers a powerful tool for improving inference and analytic transparency in qualitative research. This course introduces basic principles ...

The research themes of the Department cover machine learning and algorithms, computer networks and distributed systems ... optimization and Bayesian inference, with many trailblazing applications in ...