A. Elsaid

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it; #13,401 of 35,345 by trust here, #25,040 by citations
• Model Architectures — 28 citations into it
• Optimization & Training — 8 citations into it
• Electrical and Electronic Engineering — 7 citations into it; #12,771 of 16,539 by trust here, #15,217 by citations
• Neural Architecture Search & AutoML — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it; #14,745 of 21,575 by trust here, #19,310 by citations

Whom A. Elsaid trusts overall

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

1. Paul J. Werbos
2. Risto Miikkulainen
3. J. Urgen Schmidhuber
4. Yoshua Bengio
5. Razvan Pascanu
6. Travis Desell
7. Sepp Hochreiter
8. Message Passing Interface Forum
9. Kenneth O. Stanley
10. Geoffrey E. Hinton

Who trusts A. Elsaid overall

1. Andrés Camero
2. Enrique Alba
3. Alexander Ororbia
4. Jamal Toutouh
5. Thomas Bäck
6. Travis Desell

Papers from A. Elsaid's perspective

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

Their papers

• Evolving Recurrent Neural Networks for Time Series Data Prediction of Coal Plant Parameters (2019) — 30 citations
• Investigating recurrent neural network memory structures using neuro-evolution (2019) — 62 citations
• Using ant colony optimization to optimize long short-term memory recurrent neural networks (2018) — 30 citations