Lawrence H. Staib

Artificial Intelligence · 2000–2021

A researcher in the Science corpus: 8 papers; trusts 81 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Lawrence H. Staib trusts overall

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

  1. Geoffrey E. Hinton
  2. Alex Krizhevsky
  3. Yoshua Bengio
  4. Karen Simonyan
  5. Kaiming He
  6. Yann LeCun
  7. Diederik P. Kingma
  8. Ilya Sutskever
  9. Oriol Vinyals
  10. Ross B. Girshick

Who trusts Lawrence H. Staib overall

  1. Yvette I. Sheline

Papers from Lawrence H. Staib's perspective

Ordered by how strongly the researchers Lawrence H. Staib 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. ImageNet: A large-scale hierarchical image database
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Learning Multiple Layers of Features from Tiny Images
  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