Erik M. Schmidt

Computer Vision and Pattern Recognition · 2010–2011

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Erik M. Schmidt trusts overall

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

  1. Geoffrey E. Hinton
  2. Yoshua Bengio
  3. Simon Osindero
  4. Pascal Lamblin
  5. Yee Whye Teh
  6. Hugo Larochelle
  7. Alex Krizhevsky
  8. Radford M. Neal
  9. Yann LeCun
  10. Luis von Ahn

Who trusts Erik M. Schmidt overall

  1. Duc Le
  2. Mingyi Chen
  3. Li Deng
  4. Emily Mower Provost
  5. Xuanji He
  6. Xinxi Wang
  7. Jing Yang

Papers from Erik M. Schmidt's perspective

Ordered by how strongly the researchers Erik M. Schmidt 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  7. Learning Multiple Layers of Features from Tiny Images
  8. ImageNet: A large-scale hierarchical image database
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers