Tarik Kazaz

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it
• Signal Processing — 7 citations into it

Whom Tarik Kazaz trusts overall

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

1. Diederik P. Kingma
2. Alex Krizhevsky
3. Tim O'Shea
4. Geoffrey E. Hinton
5. Olaf Ronneberger
6. Athar Ali Khan
7. Malte Schmidt
8. Ilya Sutskever
9. Jimmy Ba
10. Erik Axell

Papers from Tarik Kazaz's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Dropout: a simple way to prevent neural networks from overfitting
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Deep Learning
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)

Their papers

• End-to-End Learning From Spectrum Data: A Deep Learning Approach for Wireless Signal Identification in Spectrum Monitoring Applications (2017) — 320 citations