Kil To Chong

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

Whom Kil To Chong trusts overall

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

  1. Martin G. Reese

Papers from Kil To Chong's perspective

Ordered by how strongly the researchers Kil To Chong 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 learning in neural networks: An overview
  8. Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
  9. Highly specific localization of promoter regions in large genomic sequences by PromoterInspector: a novel context analysis approach. (Journal of Molecular Biology)
  10. DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences

Their papers