Rafael Müller

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 204 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

Whom Rafael Müller trusts overall

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

  1. Kaiming He
  2. Alex Krizhevsky
  3. Geoffrey E. Hinton
  4. Yoshua Bengio
  5. Yann LeCun
  6. Ilya Sutskever
  7. Diederik P. Kingma
  8. Oriol Vinyals
  9. X. Zhang
  10. Ross B. Girshick

Who trusts Rafael Müller overall

  1. Zhiqiang Shen
  2. Jian Liang
  3. Diganta Misra
  4. Mitchell Wortsman
  5. Toan Q. Nguyen
  6. Hao Liu
  7. Yixiao Ge
  8. Kin Wai Lau
  9. Dapeng Hu
  10. Jianping Gou

Papers from Rafael Müller's perspective

Ordered by how strongly the researchers Rafael Müller 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. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers