Nathan Hatch

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Nathan Hatch trusts overall

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

  1. Yoshua Bengio
  2. Yann LeCun
  3. Elad Hazan
  4. Justin Domke
  5. Geoffrey E. Hinton
  6. Fabian Pedregosa
  7. Jonathan Richard Shewchuk
  8. James Bergstra
  9. Ruslan Salakhutdinov
  10. Diederik P. Kingma

Who trusts Nathan Hatch overall

  1. Xuanyi Dong
  2. Aravind Rajeswaran
  3. Chelsea Finn

Papers from Nathan Hatch's perspective

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

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

Their papers