Le-Minh Nguyen

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 191 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it; #12,317 of 35,345 by trust here, #23,077 by citations
• Natural Language Processing — 43 citations into it; #3,114 of 5,688 by trust here, #4,983 by citations
• Computer Vision and Pattern Recognition — 19 citations into it; #14,304 of 21,575 by trust here, #19,766 by citations
• Generative Models — 19 citations into it
• Model Architectures — 7 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Le-Minh Nguyen trusts overall

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

1. Tsung-Hsien Wen
2. Milica Gasic
3. Oriol Vinyals
4. Diederik P. Kingma
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. Sepp Hochreiter
8. Ilya Sutskever
9. Alex Krizhevsky
10. Tomas Mikolov

Who trusts Le-Minh Nguyen overall

1. Fei Mi
2. Van-Khanh Tran
3. Minlie Huang
4. Jiyong Zhang
5. Boi Faltings
6. Yangming Li
7. Ziwei Ji

Papers from Le-Minh Nguyen's perspective

Ordered by how strongly the researchers Le-Minh Nguyen 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. 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

• Adversarial Domain Adaptation for Variational Neural Language Generation in Dialogue Systems (2018) — 22 citations
• Dual Latent Variable Model for Low-Resource Natural Language Generation in Dialogue Systems (2018) — 13 citations
• Natural Language Generation for Spoken Dialogue System using RNN Encoder-Decoder Networks (2017) — 41 citations