T. Hong

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom T. Hong trusts overall

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

  1. Yoshua Bengio
  2. Yann LeCun
  3. Geoffrey E. Hinton
  4. Mark A. Hall
  5. Ruslan Salakhutdinov
  6. Diederik P. Kingma
  7. Nees Jan van Eck
  8. Robert Leeb
  9. L. Eon Bottou

Papers from T. Hong's perspective

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

  1. Gradient-based learning applied to document recognition
  2. Long Short-Term Memory
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Attention is All you Need (Neural Information Processing Systems)
  7. This PDF file includes: Materials and Methods
  8. A Fast Learning Algorithm for Deep Belief Nets
  9. ImageNet: A large-scale hierarchical image database
  10. Learning Multiple Layers of Features from Tiny Images

Their papers