Weijia Xu

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 299 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 90 citations into it; #31,731 of 35,345 by trust here, #30,347 by citations
• Natural Language Processing — 75 citations into it; #5,104 of 5,688 by trust here, #5,296 by citations
• Computer Vision and Pattern Recognition — 41 citations into it; #19,604 of 21,575 by trust here, #20,756 by citations
• Model Architectures — 12 citations into it
• Reinforcement Learning — 11 citations into it
• Evaluation & Benchmarks — 10 citations into it
• Machine Translation — 7 citations into it
• Molecular Biology — 7 citations into it

Whom Weijia Xu trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Jimmy Ba
4. Geoffrey E. Hinton
5. Matt Post
6. Dzmitry Bahdanau
7. Ilya Sutskever
8. Kyunghyun Cho
9. Jiatao Gu
10. Alex Krizhevsky

Who trusts Weijia Xu overall

1. Ziwei Ji
2. Marine Carpuat
3. Nayeon Lee
4. Rita Frieske
5. Tiezheng Yu

Papers from Weijia Xu's perspective

Ordered by how strongly the researchers Weijia Xu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
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. ImageNet: A large-scale hierarchical image database
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

• Rule-based Morphological Inflection Improves Neural Terminology Translation (2021) — 6 citations
• EDITOR: An Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints (2020) — 52 citations
• Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation (2019) — 10 citations