Latif Ullah Khan

Artificial Intelligence · 2017–2021

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 Latif Ullah Khan trusts overall

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

  1. Andrei V. Kelarev
  2. Virginia Smith
  3. Tian Li
  4. H. Brendan McMahan
  5. Cynthia Dwork
  6. Mingzhe Chen
  7. Walid Saad
  8. Jakub Konecný
  9. Hajime Yamamoto
  10. Takayuki Nishio

Who trusts Latif Ullah Khan overall

  1. Quoc-Viet Pham
  2. Chenhao Xu
  3. Wei Yang Bryan Lim
  4. Xuemin Shen
  5. Jiadai Wang
  6. Walid Saad
  7. Zachary MacHardy
  8. Ning Wang
  9. Luiz M. Matheus
  10. Priyanka Mary Mammen

Papers from Latif Ullah Khan's perspective

Ordered by how strongly the researchers Latif Ullah Khan 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. Gradient-based learning applied to document recognition
  4. Learning Multiple Layers of Features from Tiny Images
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. ImageNet: A large-scale hierarchical image database
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Going deeper with convolutions

Their papers