Search Results for author: Zihuai He

Found 3 papers, 1 papers with code

Ensembling improves stability and power of feature selection for deep learning models

no code implementations2 Oct 2022 Prashnna K Gyawali, Xiaoxia Liu, James Zou, Zihuai He

Despite extensive recent efforts to define different feature importance metrics for deep learning models, we identified that inherent stochasticity in the design and training of deep learning models makes commonly used feature importance scores unstable.

Feature Importance feature selection

Improving genetic risk prediction across diverse population by disentangling ancestry representations

no code implementations10 May 2022 Prashnna K Gyawali, Yann Le Guen, Xiaoxia Liu, Hua Tang, James Zou, Zihuai He

This can lead to biases in the risk predictors resulting in poor generalization when applied to minority populations and admixed individuals such as African Americans.

Genetic Risk Prediction

Deep neural networks with controlled variable selection for the identification of putative causal genetic variants

1 code implementation29 Sep 2021 Peyman H. Kassani, Fred Lu, Yann Le Guen, Zihuai He

The merit of the proposed method includes: (1) flexible modelling of the non-linear effect of genetic variants to improve statistical power; (2) multiple knockoffs in the input layer to rigorously control false discovery rate; (3) hierarchical layers to substantially reduce the number of weight parameters and activations to improve computational efficiency; (4) de-randomized feature selection to stabilize identified signals.

Computational Efficiency feature selection +1

Cannot find the paper you are looking for? You can Submit a new open access paper.