Mingqian Tang

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Mingqian Tang trusts overall

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

  1. Diederik P. Kingma
  2. João Carreira
  3. Andrew Zisserman
  4. Geoffrey E. Hinton
  5. Jimmy Ba
  6. Kaiming He

Papers from Mingqian Tang's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Going deeper with convolutions
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers