Ahmed Mustafa

Signal Processing · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ahmed Mustafa trusts overall

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

  1. Diederik P. Kingma
  2. Jean-Marc Valin
  3. Yoshua Bengio
  4. Jimmy Ba
  5. Ryan J. Prenger
  6. Christophe Veaux
  7. Geoffrey E. Hinton
  8. Fabian Mentzer
  9. Aäron van den Oord
  10. Alex Krizhevsky

Papers from Ahmed Mustafa's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Going deeper with convolutions
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers