Weiyue Wang
Artificial Intelligence · with Ney · 2016–2019
A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 16 citations into it; #17,346 of 35,345 by trust here, #18,186 by citations
- Natural Language Processing — 11 citations into it; #3,046 of 5,688 by trust here, #3,638 by citations
- Evaluation & Benchmarks — 10 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it; #10,992 of 21,575 by trust here, #12,172 by citations
Whom Weiyue Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ondrej Bojar
- Miloš Stanojević
- Matous Machácek
- Matthew G. Snover
- Amir Kamran
- Philipp Koehn
- Diederik P. Kingma
- Taku Kudo
- Yvette Graham
- Salim Roukos
Who trusts Weiyue Wang overall
- M. V. Koroteev
- Ondrej Bojar
- Jan Niehues
- Pierre Colombo
- Franck Burlot
- Hiroki Shimanaka
- Marcis Pinnis
- Nitika Mathur
- Yvette Graham
- Thomas Zenkel
Papers from Weiyue Wang's perspective
Ordered by how strongly the researchers Weiyue Wang trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Bleu: a Method for Automatic Evaluation of Machine Translation
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Neural Machine Translation of Rare Words with Subword Units
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- CharacTer: Translation Edit Rate on Character Level (2016) — 156 citations
- Analysis of Positional Encodings for Neural Machine Translation (2019) — 21 citations