Yuzong Liu
Artificial Intelligence · 2019–2020
A researcher in the Science corpus: 3 papers; trusts 112 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 56 citations into it; #9,824 of 35,345 by trust here, #12,244 by citations
- Signal Processing — 30 citations into it; #1,746 of 7,572 by trust here, #1,820 by citations
- Natural Language Processing — 28 citations into it; #3,237 of 5,688 by trust here, #4,250 by citations
- Speech & Audio — 26 citations into it; #567 of 1,076 by trust here, #642 by citations
- Representation & Self-Supervised Learning — 19 citations into it; #1,859 of 3,145 by trust here, #2,042 by citations
- Computer Vision and Pattern Recognition — 10 citations into it
- Model Architectures — 9 citations into it
- Large Language Models — 5 citations into it
Whom Yuzong Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Yu-An Chung
- Alex Graves
- Oriol Vinyals
- Diederik P. Kingma
- Alexei Baevski
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
Who trusts Yuzong Liu overall
- Jasha Droppo
- Yu-An Chung
- Puyuan Peng
- Oguz H. Elibol
- Shaoshi Ling
- Alexander H. Liu
- Abdel-rahman Mohamed
- Wei-Ning Hsu
- Andy T. Liu
- Hung-yi Lee
Papers from Yuzong Liu's perspective
Ordered by how strongly the researchers Yuzong Liu 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Deep Contextualized Acoustic Representations for Semi-Supervised Speech Recognition (2019) — 150 citations
- DeCoAR 2.0: Deep Contextualized Acoustic Representations with Vector Quantization (2020) — 117 citations
- Neural Text Normalization with Subword Units (2019) — 42 citations