Mohammad A. Gowayyed

Artificial Intelligence · 2015

A researcher in the Science corpus: 1 paper; trusts 35 researchers and is trusted by 58 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #3,847 of 35,345 by trust here, #8,283 by citations
• Signal Processing — 16 citations into it; #588 of 7,572 by trust here, #981 by citations
• Natural Language Processing — 14 citations into it
• Speech & Audio — 12 citations into it; #171 of 1,076 by trust here, #350 by citations
• Model Architectures — 8 citations into it

Whom Mohammad A. Gowayyed trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Andrew L. Maas
4. Sepp Hochreiter
5. Yoshua Bengio
6. Yajie Miao
7. J. Urgen Schmidhuber
8. Hank Liao
9. Abdel-rahman Mohamed
10. Oriol Vinyals

Who trusts Mohammad A. Gowayyed overall

1. Takaaki Hori
2. Jinyu Li
3. Yonatan Belinkov
4. Shinji Watanabe
5. Shaoshi Ling
6. Kartik Audhkhasi
7. Gakuto Kurata
8. Weiran Wang
9. Ronan Collobert
10. Jan Chorowski

Papers from Mohammad A. Gowayyed's perspective

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

1. Long Short-Term Memory
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding (2015) — 788 citations