Surafel Melaku Lakew

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 4 papers; trusts 197 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 108 citations into it; #10,294 of 35,345 by trust here, #16,166 by citations
• Natural Language Processing — 102 citations into it; #2,043 of 5,688 by trust here, #3,478 by citations
• Computer Vision and Pattern Recognition — 66 citations into it
• Evaluation & Benchmarks — 17 citations into it
• Model Architectures — 15 citations into it
• Machine Translation — 13 citations into it
• Optimization & Training — 13 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Surafel Melaku Lakew trusts overall

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

1. Diederik P. Kingma
2. Rico Sennrich
3. Yoshua Bengio
4. Ilya Sutskever
5. Geoffrey E. Hinton
6. Kyunghyun Cho
7. Dzmitry Bahdanau
8. Alex Krizhevsky
9. Jimmy Ba
10. Barret Zoph

Who trusts Surafel Melaku Lakew overall

1. Raj Dabre
2. Biao Zhang
3. Mattia Antonino Di Gangi
4. Surangika Ranathunga
5. Matteo Negri
6. Roee Aharoni
7. Chenhui Chu
8. Philip Williams
9. Alexandra Chronopoulou
10. Marco Turchi

Papers from Surafel Melaku Lakew's perspective

Ordered by how strongly the researchers Surafel Melaku Lakew 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. 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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Multilingual Neural Machine Translation for Zero-Resource Languages (2019) — 14 citations
• A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation (2018) — 111 citations
• Transfer Learning in Multilingual Neural Machine Translation with Dynamic Vocabulary (2018) — 72 citations
• Adapting Multilingual Neural Machine Translation to Unseen Languages (2019) — 21 citations