Tianqi Tang

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 94 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tianqi Tang trusts overall

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

  1. Ross B. Girshick
  2. Kaiming He
  3. Alex Krizhevsky
  4. Shaoqing Ren
  5. Geoffrey E. Hinton
  6. Yann LeCun
  7. Karen Simonyan
  8. Yoshua Bengio
  9. Andrew Zisserman
  10. Ilya Sutskever

Papers from Tianqi Tang's perspective

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

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

Their papers