Tae-young Kim

Artificial Intelligence · with Kim · 2019

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tae-young Kim trusts overall

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

  1. Tomas Mikolov
  2. Miltiadis Allamanis
  3. Geoffrey E. Hinton

Papers from Tae-young Kim's perspective

Ordered by how strongly the researchers Tae-young Kim trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Gradient-based learning applied to document recognition
  2. ImageNet classification with deep convolutional neural networks
  3. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
  4. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
  5. Efficient Estimation of Word Representations in Vector Space
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Long Short-Term Memory
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers