Hilal Tayara

Molecular Biology · 2019

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 16 citations into it
• Artificial Intelligence — 5 citations into it

Whom Hilal Tayara trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Martin G. Reese
2. Diederik P. Kingma
3. Mike Schuster
4. Thomas A. Down

Papers from Hilal Tayara's perspective

Ordered by how strongly the researchers Hilal Tayara trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Going deeper with convolutions
4. Deep Learning
5. Deep Sparse Rectifier Neural Networks
6. Bidirectional recurrent neural networks
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Long Short-Term Memory
9. Deep learning in neural networks: An overview
10. Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

Their papers

• DeePromoter: Robust Promoter Predictor Using Deep Learning (2019) — 171 citations