Ming Zhong

Artificial Intelligence · with Liu · 2019–2022

A researcher in the Science corpus: 5 papers; trusts 101 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

Whom Ming Zhong trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Yoshua Bengio
  4. Oriol Vinyals
  5. Ilya Sutskever
  6. Chin-Yew Lin
  7. Alex Krizhevsky
  8. Richard Socher
  9. Tomas Mikolov
  10. Yann LeCun

Who trusts Ming Zhong overall

  1. Yixin Liu
  2. Pengfei Liu
  3. Danqing Wang
  4. Yiran Chen
  5. Xipeng Qiu
  6. Peng Liu
  7. Zi-Yi Dou
  8. L. Elisa Celis
  9. Xiang Lisa Li
  10. Yi Tay

Papers from Ming Zhong's perspective

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

Their papers