partial-information-decomposition

The paper introduces ePID, a scalable pipeline using supervised embeddings to compute partial information decomposition for symptom networks, enabling the separation of redundant and synergistic information in mental health data.

This paper proposes a Partial Information Decomposition framework to select the most informative pair of MRI contrasts for brain tumor segmentation using lightweight 3D U-Nets, reducing computational cost while maintaining performance.