S. Latif

Statistical and Nonlinear Physics · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom S. Latif trusts overall

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

  1. Karen Simonyan
  2. Kaiming He
  3. Individualized Treat
  4. Ioannis D. Apostolopoulos
  5. Yi Zhu
  6. Kit-Kay Mak
  7. Andrew Zisserman
  8. Geoffrey E. Hinton
  9. Mücahid Barstuğan
  10. X. Zhang

Papers from S. Latif's perspective

Ordered by how strongly the researchers S. Latif 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  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. ImageNet: A large-scale hierarchical image database
  8. GENERATIVE ADVERSARIAL NETS
  9. Attention is All you Need (Neural Information Processing Systems)
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers