Xin Jin

Artificial Intelligence · USENIX Symposium on Operating Systems Design and Implementation · 2017–2024

A researcher in the Science corpus: 6 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Xin Jin trusts overall

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

  1. Michael M. Mitzenmacher
  2. Brett D. Fleisch
  3. E.J. Candes
  4. Diego Ongaro
  5. Robbert van Renesse
  6. Graham Cormode
  7. Frank Dabek
  8. Patrick Hunt
  9. Joseph Dean
  10. Yin Zhang

Who trusts Xin Jin overall

  1. Anuj Kalia
  2. Michael Kaminsky

Papers from Xin Jin's perspective

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

Their papers