Moonbin Yim

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Moonbin Yim trusts overall

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

  1. Diederik P. Kingma
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Ronald J. Williams
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Ross B. Girshick
  8. Jimmy Ba
  9. Jia Deng
  10. Yann LeCun

Papers from Moonbin Yim's perspective

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

Their papers