latent variable models

Understanding the complexity of cancer requires making sense of equally complex biological data. In our lab, we develop probabilistic models for the integration of multi-omics datasets to uncover hidden structure in the data by capturing both shared and modality-specific sources of variation.

A multi-view latent variable model with structured sparsity that integrates noisy domain expertise in terms of feature sets.

Probabilistic machine learning for uncertainty-aware deep latent variable models