135 citations · 572 across the 19 of their papers we have counts for
19 papers
Learning to Stop While Learning to Predict
Xinshi Chen, Hanjun Dai, Yu Li +2
There is a recent surge of interest in designing deep architectures based on the update steps in traditional algorithms, or learning neural networks to improve and replace traditio…
RNA Secondary Structure Prediction By Learning Unrolled Algorithms
Xinshi Chen, Yu Li, Ramzan Umarov +2
In this paper, we propose an end-to-end deep learning model, called E2Efold, for RNA secondary structure prediction which can effectively take into account the inherent constraints…
Deep learning in bioinformatics: introduction, application, and perspective in big data era
Yu Li, Chao Huang, Lizhong Ding +3
Deep learning, which is especially formidable in handling big data, has achieved great success in various fields, including bioinformatics. With the advances of the big data era in…
PromID: human promoter prediction by deep learning
Ramzan Umarov, Hiroyuki Kuwahara, Yu Li +2
Computational identification of promoters is notoriously difficult as human genes often have unique promoter sequences that provide regulation of transcription and interaction with…
Accelerating Flash Calculation through Deep Learning Methods
Yu Li, Tao Zhang, Shuyu Sun +1
In the past two decades, researchers have made remarkable progress in accelerating flash calculation, which is very useful in a variety of engineering processes. In this paper, gen…
On the Decision Boundary of Deep Neural Networks
Yu Li, Lizhong Ding, Xin Gao
While deep learning models and techniques have achieved great empirical success, our understanding of the source of success in many aspects remains very limited. In an attempt to b…