Nasir Hayat

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Optimization & Training — 7 citations into it
• Model Architectures — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Nasir Hayat trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Sergey Ioffe
6. Diederik P. Kingma
7. Christian Szegedy
8. Ross B. Girshick
9. Andrew Zisserman
10. Ekin Dogus Cubuk

Papers from Nasir Hayat's perspective

Ordered by how strongly the researchers Nasir Hayat 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. Long Short-Term Memory
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Towards Robust and Reproducible Active Learning using Neural Networks (2020) — 89 citations