Matt Johnson

Optimization & Training · with Ba · 2018

A researcher in the Science corpus: 1 paper; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Matt Johnson trusts overall

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

  1. James Martens
  2. Yoshua Bengio
  3. Diederik P. Kingma
  4. Ilya Sutskever
  5. Geoffrey E. Hinton
  6. Jimmy Ba
  7. Roger Baker Grosse
  8. Razvan Pascanu
  9. Sepp Hochreiter
  10. Alex Graves

Who trusts Matt Johnson overall

  1. Sidak Pal Singh
  2. Michael Matena
  3. Naman Agarwal

Papers from Matt Johnson's perspective

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

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

Their papers