Shiwen Wu
Artificial Intelligence · 2020–2022
A researcher in the Science corpus: 2 papers; trusts 63 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 130 citations into it; #34,575 of 35,345 by trust here, #19,439 by citations
- Information Systems — 108 citations into it; #8,517 of 8,771 by trust here, #3,876 by citations
- Computer Vision and Pattern Recognition — 44 citations into it
- Management Science and Operations Research — 28 citations into it
- Recommender Systems — 26 citations into it
- Graph Learning — 19 citations into it
- Model Architectures — 15 citations into it
- Knowledge Graphs & Representation — 5 citations into it
Whom Shiwen Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Sepp Hochreiter
- Xiangnan He
- Alex Krizhevsky
- Yehuda Koren
- Yann LeCun
- Ilya Sutskever
- Ruslan Salakhutdinov
Who trusts Shiwen Wu overall
- Junliang Yu
- Xin Zhou
- Zihan Lin
- Chongming Gao
- Hongzhi Yin
- Yupeng Hou
- Xin Xia
- Changxin Tian
- Wenqiang Lei
Papers from Shiwen Wu's perspective
Ordered by how strongly the researchers Shiwen Wu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Contrastive Learning for Sequential Recommendation (2022) — 559 citations
- Graph Neural Networks in Recommender Systems: A Survey (2020) — 1,821 citations