Boxing Chen

Artificial Intelligence · with Cao · 2021

A researcher in the Science corpus: 2 papers; trusts 94 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 64 citations into it
• Computer Vision and Pattern Recognition — 39 citations into it
• Natural Language Processing — 38 citations into it
• Optimization & Training — 8 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Boxing Chen trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Kaiming He
5. Jimmy Ba
6. Alex Krizhevsky
7. Ilya Sutskever
8. Yann LeCun
9. Alex Graves
10. Oriol Vinyals

Papers from Boxing Chen's perspective

Ordered by how strongly the researchers Boxing Chen 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Adaptive Adapters: An Efficient Way to Incorporate BERT Into Neural Machine Translation (2021) — 26 citations
• Continual Learning for Neural Machine Translation (2021) — 34 citations