Search Results for author:
Found 6 papers, 3 papers with code
Label Informed Contrastive Pretraining for Node Importance Estimation on Knowledge Graphs
Considering the NIE problem, LICAP adopts a novel sampling strategy called top nodes preferred hierarchical sampling to first group all interested nodes into a top bin and a non-top bin based on node importance scores, and then divide the nodes within top bin into several finer bins also based on the scores.
scDiffusion: conditional generation of high-quality single-cell data using diffusion model
This strategy allows the model to generate continuous trajectories of cell development from a given cell state.
xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data
Advances in high-throughput sequencing technology have led to significant progress in measuring gene expressions at the single-cell level.
MMA-RNN: A Multi-level Multi-task Attention-based Recurrent Neural Network for Discrimination and Localization of Atrial Fibrillation
The automatic detection of atrial fibrillation based on electrocardiograph (ECG) signals has received wide attention both clinically and practically.
$\textit{Ab Initio}$ Discovery of Biological Knowledge from scRNA-Seq Data Using Machine Learning
The study illustrated the feasibility, significance, and limitation of $\textit{ab initio}$ ML knowledge discovery on complex biological problems.
Generation of Synthetic Electronic Medical Record Text
It can also be used as a data augmentation method to assist studies based on real EMR data.
