Shauna Revay

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Shauna Revay trusts overall

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

  1. Diederik P. Kingma
  2. Xavier Glorot
  3. O. Ureten
  4. Djork-Arné Clevert
  5. Tim O'Shea
  6. Yoshua Bengio
  7. Jimmy Ba

Papers from Shauna Revay's perspective

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

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

Their papers