Search Results for author:
Found 3 papers, 2 papers with code
CADA-GAN: Context-Aware GAN with Data Augmentation
Current child face generators are restricted by the limited size of the available datasets.
Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks
In this paper, we introuduce graph feature to feature (Fea2Fea) prediction pipelines in a low dimensional space to explore some preliminary results on structural feature correlation, which is based on graph neural network.
Ranked #1 on
Graph Classification
on Pubmed
Variational Autoencoder for Anti-Cancer Drug Response Prediction
Additionally, we show that our model can generates effective drug compounds not previously used for specific cancer cell lines.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
