Xiangzhan Yu
Artificial Intelligence · 2020–2021
A researcher in the Science corpus: 3 papers; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 83 citations into it
- Natural Language Processing — 38 citations into it
- Computer Vision and Pattern Recognition — 35 citations into it
- Signal Processing — 27 citations into it
- Optimization & Training — 12 citations into it
- Computational Mechanics — 6 citations into it
Whom Xiangzhan Yu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- James Martens
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Ilya Sutskever
- Yann LeCun
- Oriol Vinyals
- Kaiming He
- Alex Graves
Papers from Xiangzhan Yu's perspective
Ordered by how strongly the researchers Xiangzhan Yu trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Distilling the Knowledge in a Neural Network (arXiv.org)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Unispeech-Sat: Universal Speech Representation Learning With Speaker Aware Pre-Training (2021) — 138 citations
- Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting (2020) — 270 citations
- Ultra Fast Speech Separation Model with Teacher Student Learning (2021) — 15 citations