Joseph C. Park

This paper introduces Generative Manifold Networks (GMNs) for modeling complex system dynamics, demonstrating their ability to predict and simulate chaotic and neural dynamics with explainability.

The paper shows that causal relationships can exist in transcriptional networks without correlation, using nonlinear causality tests to detect uncorrelated causal links in yeast and mouse.