In today's scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly increasing ...

Approaches for statistical inference -- The Bayes approach -- Bayesian computation -- Model criticism and selection -- The empirical Bayes approach -- Bayesian design -- Special methods and models -- ...

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 ...

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 ...

The FDA's move to incorporate Bayesian statistical methods into clinical trials of drugs and biologics garnered special treatment in JAMA this week. JAMA published three perspectives -- two welcoming ...

How can artificial intelligence improve the analysis of chromatographic data? Artificial intelligence (AI) is a powerful and ...

Rochester Institute of Technology researchers are taking on Big Data to reduce the negative impact of faulty measurements in data collected from complex sensing systems. "Based on tremendous ...