Nature

Residual bayesian attention networks for uncertainty quantification in regression tasks

The demand for uncertainty quantification in modern sequence modeling tasks has prompted researchers to explore deep integration between Bayesian inference and Transformer architectures, but existing ...
Nature

Uncovering hidden and complex relations of pandemic dynamics using an AI driven system

The COVID-19 pandemic continues to challenge healthcare systems globally, necessitating advanced tools for clinical decision support. Amidst the complexity of COVID-19 symptomatology and disease ...
mccormick.northwestern.edu

MLDS 490: Bayesian Methods for Inference and Decision Making

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 ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...