Van-Khanh Tran

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; #12,318 of 35,345 by trust here, #23,077 by citations
• Natural Language Processing — 43 citations into it; #3,115 of 5,688 by trust here, #4,983 by citations
• Computer Vision and Pattern Recognition — 19 citations into it; #14,305 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 Van-Khanh Tran 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. Paul J. Werbos

Who trusts Van-Khanh Tran overall

1. Fei Mi
2. Minlie Huang
3. Le-Minh Nguyen
4. Jiyong Zhang
5. Boi Faltings
6. Yangming Li
7. Ziwei Ji
8. Kaisheng Yao
9. Kun Qian
10. Liangwei Chen

Papers from Van-Khanh Tran's perspective

Ordered by how strongly the researchers Van-Khanh Tran trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
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