Michaela Blott

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 4 papers; trusts 202 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Michaela Blott trusts overall

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

  1. Alex Krizhevsky
  2. Yoshua Bengio
  3. Geoffrey E. Hinton
  4. Kaiming He
  5. Karen Simonyan
  6. Yann LeCun
  7. Ilya Sutskever
  8. Song Han
  9. Matthieu Courbariaux
  10. Sergey Ioffe

Who trusts Michaela Blott overall

  1. Manuele Rusci
  2. Md Maruf Hossain Shuvo
  3. Zhen Dong

Papers from Michaela Blott's perspective

Ordered by how strongly the researchers Michaela Blott 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: A large-scale hierarchical image database
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers