Microsoft Research

Artificial Intelligence · 2009–2023

A researcher in the Science corpus: 5 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Microsoft Research trusts overall

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

  1. Zachary Chase Lipton
  2. Q. Liao
  3. Upol Ehsan
  4. Brian Y. Lim
  5. Marco Tulio Ribeiro
  6. David Alvarez-Melis
  7. R. Caruana
  8. Geoffrey E. Hinton
  9. Been Kim
  10. Tim Miller

Papers from Microsoft Research's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Attention is All you Need (Neural Information Processing Systems)
  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. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
  8. ImageNet: A large-scale hierarchical image database
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Learning Multiple Layers of Features from Tiny Images

Their papers