The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...