Moo Jin Kim

Artificial Intelligence · 2023–2025

A researcher in the Science corpus: 5 papers; trusts 96 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Moo Jin Kim trusts overall

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

  1. Geoffrey E. Hinton
  2. Diederik P. Kingma
  3. Alex Krizhevsky
  4. Kaiming He
  5. Yoshua Bengio
  6. Ilya Sutskever
  7. Yann LeCun
  8. Quoc V. Le
  9. Ross B. Girshick
  10. Sergey Levine

Who trusts Moo Jin Kim overall

  1. Qingwen Bu
  2. Yueen Ma
  3. Chelsea Finn
  4. Michał Zawalski
  5. Jihan Yang
  6. Songming Liu

Papers from Moo Jin Kim's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Attention is All you Need (Neural Information Processing Systems)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Long Short-Term Memory
  6. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers