Uiuc MIT-IBM

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Uiuc MIT-IBM trusts

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

  1. Kaiming He (in Computer Vision and Pattern Recognition)
  2. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  3. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  4. X. Zhang (in Computer Vision and Pattern Recognition)
  5. Oriol Vinyals (in Artificial Intelligence)
  6. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
  7. Devi Parikh (in Computer Vision and Pattern Recognition)
  8. Li Fei-Fei (in Computer Vision and Pattern Recognition)
  9. C. Lawrence Zitnick (in Computer Vision and Pattern Recognition)
  10. Andrew Zisserman (in Computer Vision and Pattern Recognition)

Papers from Uiuc MIT-IBM's perspective

Ordered by how strongly the researchers Uiuc MIT-IBM 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  3. ImageNet classification with deep convolutional neural networks
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Gradient-based learning applied to document recognition
  8. Representation Learning with Contrastive Predictive Coding
  9. ImageNet: A large-scale hierarchical image database
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers