Min Liu

Artificial Intelligence · with Ma · 2021

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Min Liu trusts overall

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

  1. David Snyder
  2. Daniel Povey
  3. Jiankang Deng
  4. Joon Son Chung
  5. Arsha Nagrani
  6. Andrew Zisserman
  7. Tom Ko

Papers from Min Liu's perspective

Ordered by how strongly the researchers Min Liu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. Long Short-Term Memory
  8. Going deeper with convolutions
  9. Gradient-based learning applied to document recognition
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers