Causal modeling enables robust counterfactual reasoning and interventional mechanisms to make predictions across different hypothetical scenarios. Nevertheless, uncoverin[...]

This research investigates the intersection of applied statistics, machine learning, and healthcare to leverage the quantitative approaches as a means of improving patien[...]

Outages that occur in power distribution systems can seriously endanger system operation in different ways. In recent years, with the explosion in data gathering within t[...]

Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a sequence model th[...]