A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

2024 - Bristol-Meyers Squibb was awarded for “PMI Prediction and Bayesian Optimization: Two Tools with One Goal Towards the Development of ‘Greener-by-Design’ Synthesis of APIs” Read more about BMS’s ...

We propose a Bayesian panel model for mixed frequency data, where parameters can change over time according to a Markov process. Our model allows for both structural instability and random effects. To ...

This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...