SAE-IBS (Singular Autoencoder generalized by an IBS similarity matrix), combines the strengths of traditional matrix decomposition-based (e.g., principal component analysis) and more recent neural network-based (e.g., autoencoders) solutions. I.e., it yields an orthogonal latent space enhancing dimensionality selection while learning non-linear transformations.
- Construction of Robust Ancestry Space in the Presence of Relatedness
- Robust Projection of Target Data onto Reference Ancestry Space
Hybrid Autoencoder with Orthogonal Latent Space for Robust Population Structure Inference