Explainable Algorithms

A novel convolutional filter-based approach for learning mutation signature representations.

Developing interpretable deep neural network approaches for dimensionality reduction that embed functional ANOVA decompositions within variational autoencoders.

Unravelling the history of genomic instability through deep reinforcement learning.

Developing automated learning frameworks for reproducible and transferable biological data analysis.