Adriana Romero Soriano

McGill University
Session: machine learning in neuroscience

 

Deep learning for genomics and graph-structured data

In recent years, deep learning has achieved promising results in medical imaging analysis. However, in order to fullyexploit the richness of healthcare data, new models able to deal with a variety of modalities have to be designed.

In this talk, I will discuss recent advances in deep learning for genomics and graph-structured data. I will present Diet Networks, a recent contribution which copes with the high dimensionality of genomic data. Then, I will introduce our work on Graph Attention Networks, which has recently shown to improve results on protein-protein interaction networks and mesh-based parcellation of the cerebral cortex.