Renyu Yang
Artificial Intelligence · 2020
A researcher in the Science corpus: 2 papers; trusts 83 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 205 citations into it
- Natural Language Processing — 142 citations into it
- Computer Vision and Pattern Recognition — 42 citations into it
- Model Architectures — 38 citations into it
- Representation & Self-Supervised Learning — 26 citations into it
- Information Systems — 24 citations into it
- Large Language Models — 18 citations into it
- Graph Learning — 16 citations into it
Whom Renyu Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thorsten Joachims
- Richard Socher
- Geoffrey E. Hinton
- Yoshua Bengio
- Tomas Mikolov
- Kaiming He
- Diederik P. Kingma
- Alex Krizhevsky
- Yann LeCun
- Ilya Sutskever
Papers from Renyu Yang's perspective
Ordered by how strongly the researchers Renyu Yang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- A Survey on Text Classification: From Shallow to Deep Learning (2020) — 173 citations
- A Survey on Text Classification: From Traditional to Deep Learning (2020) — 549 citations