FURI | Summer 2020

Learning and Sampling from the Causal Graph of Multi Categorical Distributions Via the Generative Adversarial Network

Machine learning is being used to solve many problems, trying to generate multi categorical data is one of the challenges the researchers faced. The researcher team has proposed a new method to solve this specific problem based on a previous structure and tried to examine if the new method is superior by using multiple metrics to measure the performance. Due to the time limit and COVID pandemic restrictions, the work to generate a final result is still in progress.