Fred Roosta

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 41 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Fred Roosta trusts overall

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

  1. Alex Krizhevsky
  2. Yoshua Bengio
  3. Rie Johnson
  4. Jorge Nocedal
  5. Geoffrey E. Hinton
  6. David Chin-Lung Fong
  7. Tong Zhang
  8. Diederik P. Kingma
  9. Sou-Cheng T. Choi
  10. Michael A. Saunders

Papers from Fred Roosta's perspective

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

Their papers