Xavier Giró-i-Nieto

Deep Variational Autoencoders for Population Genetics

This paper applies variational autoencoders to genomic data to capture population structure, enable dimensionality reduction, and improve data compression across diverse populations.

Neural ADMIXTURE: rapid population clustering with autoencoders

Neural ADMIXTURE uses an autoencoder to rapidly cluster large genetic datasets, reducing computation time compared to traditional methods like ADMIXTURE.

Predicting Dog Phenotypes from Genotypes

This paper predicts dog phenotypes (breed, height, weight) from genotypes using linear and non-linear methods, showing that linear methods outperform non-linear for breed classification but not for height and weight regression.

Generative Moment Matching Networks for Genotype Simulation

This paper uses Generative Moment Matching Networks to simulate SNP sequences and introduces training improvements and evaluation metrics.