Mahmood Yousefi-Azar

Artificial Intelligence · 2017

A researcher in the Science corpus: 2 papers; trusts 115 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 36 citations into it
• Representation & Self-Supervised Learning — 17 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Signal Processing — 13 citations into it
• Natural Language Processing — 9 citations into it
• Information Systems — 7 citations into it
• Model Architectures — 7 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Mahmood Yousefi-Azar trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Ruslan Salakhutdinov
4. Alex Krizhevsky
5. Pascal Vincent
6. Quoc V. Le
7. Yann LeCun
8. Hugo Larochelle
9. Diederik P. Kingma
10. Ilya Sutskever

Who trusts Mahmood Yousefi-Azar overall

1. Zexian Zeng
2. Ke He
3. Daniel S. Berman
4. Javed Asharf
5. Mohammed Ali Al-Garadi
6. Sheraz Naseer
7. Muhammad Usama
8. Yu Deng
9. Dan Dongseong Kim
10. Anna L. Buczak

Papers from Mahmood Yousefi-Azar's perspective

Ordered by how strongly the researchers Mahmood Yousefi-Azar 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. 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. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Autoencoder-based feature learning for cyber security applications (2017) — 300 citations
• Text summarization using unsupervised deep learning (2017) — 232 citations