5 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 5 cited
Ensembling improves stability and power of feature selection for deep learning models
Prashnna K Gyawali, Xiaoxia Liu, James Zou +1
With the growing adoption of deep learning models in different real-world domains, including computational biology, it is often necessary to understand which data features are esse…
cs.LG2022★ 1 cited
Improving genetic risk prediction across diverse population by disentangling ancestry representations
Prashnna K Gyawali, Yann Le Guen, Xiaoxia Liu +3
Risk prediction models using genetic data have seen increasing traction in genomics. However, most of the polygenic risk models were developed using data from participants with sim…
cs.LG2021
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants
Peyman H. Kassani, Fred Lu, Yann Le Guen +1
Deep neural networks (DNN) have been used successfully in many scientific problems for their high prediction accuracy, but their application to genetic studies remains challenging…