DAG Learning from Zero-Inflated Count Data Using Continuous Optimization

This article likely presents a novel approach to learning Directed Acyclic Graphs (DAGs) from count data that has an excess of zero values (zero-inflated). The use of continuous optimization suggests a computational method for estimating the DAG structure. The source, ArXiv, indicates this is a pre-print or research paper.