Muhammad Bilal

Artificial Intelligence · 2016–2023

A researcher in the Science corpus: 6 papers; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Muhammad Bilal trusts overall

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

  1. Muthu Dayalan
  2. Geoffrey E. Hinton
  3. Xiaomo Jiang
  4. Yoshua Bengio
  5. Alex Krizhevsky
  6. Ian J. Goodfellow
  7. Yann LeCun
  8. Xindong Wu
  9. Diederik P. Kingma
  10. Lovedeep Gondara

Papers from Muhammad Bilal's perspective

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

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

Their papers