Yuexin Wu
Artificial Intelligence · with Yang · 2016–2022
A researcher in the Science corpus: 5 papers; trusts 212 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 126 citations into it; #16,816 of 35,345 by trust here, #8,157 by citations
- Computer Vision and Pattern Recognition — 65 citations into it
- Natural Language Processing — 54 citations into it
- Representation & Self-Supervised Learning — 19 citations into it
- Evaluation & Benchmarks — 18 citations into it
- Information Systems — 11 citations into it; #6,127 of 8,771 by trust here, #5,303 by citations
- Model Architectures — 11 citations into it
- Graph Learning — 10 citations into it
Whom Yuexin Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Diederik P. Kingma
- Alex Graves
- Richard Socher
- Oriol Vinyals
- Alex Krizhevsky
- Yann LeCun
- Jason Aaron Edward Weston
Who trusts Yuexin Wu overall
- Seyed Mehran Kazemi
- Hongwei Wang
- Shervin Minaee
- Erik Cambria
- Ilias Chalkidis
- Zhanqiu Zhang
- Weiwei Liu
- Peter Anderson
- Rishab Goel
- Shaoxiong Ji
Papers from Yuexin Wu's perspective
Ordered by how strongly the researchers Yuexin Wu 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Large Language Models Can Self-Improve (2022) — 879 citations
- StoryGAN: A Sequential Conditional GAN for Story Visualization (2018) — 299 citations
- Deep Learning for Extreme Multi-label Text Classification (2017) — 735 citations
- Analogical Inference for Multi-relational Embeddings (2017) — 406 citations
- Review Networks for Caption Generation (2016) — 268 citations