Cong Duy Vu Hoang

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 82 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 44 citations into it; #13,579 of 35,345 by trust here, #14,181 by citations
• Natural Language Processing — 41 citations into it; #2,535 of 5,688 by trust here, #3,014 by citations
• Computer Vision and Pattern Recognition — 23 citations into it; #10,002 of 21,575 by trust here, #10,500 by citations
• Model Architectures — 14 citations into it

Whom Cong Duy Vu Hoang trusts overall

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

1. Rico Sennrich
2. Ilya Sutskever
3. Kyunghyun Cho
4. Yoshua Bengio
5. Sepp Hochreiter
6. Geoffrey E. Hinton
7. Dzmitry Bahdanau
8. Oriol Vinyals
9. Alex Graves
10. J. Urgen Schmidhuber

Who trusts Cong Duy Vu Hoang overall

1. Sachin Kumar
2. Sneha Kudugunta
3. Felix Stahlberg
4. Tom Kocmi
5. Shantipriya Parida
6. Jason Lee
7. Hao Hao Tan
8. Faisal Ladhak
9. Yu Li
10. Timo Schick

Papers from Cong Duy Vu Hoang's perspective

Ordered by how strongly the researchers Cong Duy Vu Hoang 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. Attention is All you Need (Neural Information Processing Systems)
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

• Incorporating Side Information into Recurrent Neural Network Language Models (2016) — 35 citations
• Iterative Back-Translation for Neural Machine Translation (2018) — 342 citations
• Towards Decoding as Continuous Optimisation in Neural Machine Translation (2017) — 44 citations