Shu-Wen Yang
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 4 papers; trusts 41 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 127 citations into it; #16,544 of 35,345 by trust here, #8,619 by citations
- Signal Processing — 76 citations into it; #3,733 of 7,572 by trust here, #2,052 by citations
- Speech & Audio — 65 citations into it; #533 of 1,076 by trust here, #371 by citations
- Natural Language Processing — 47 citations into it
- Representation & Self-Supervised Learning — 36 citations into it
- Computer Vision and Pattern Recognition — 23 citations into it
- Optimization & Training — 6 citations into it
Whom Shu-Wen Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Jimmy Ba
- Alex Krizhevsky
- Ilya Sutskever
- Alexei Baevski
- Alex Graves
- Kaiming He
- Yann LeCun
Who trusts Shu-Wen Yang overall
- Yu-An Chung
- Puyuan Peng
- Sanyuan Chen
- Yuan Gong
- Lasse Borgholt
- Abdel-rahman Mohamed
- Hung-yi Lee
- James R. Glass
- David F. Harwath
- Ankita Pasad
Papers from Shu-Wen Yang's perspective
Ordered by how strongly the researchers Shu-Wen Yang 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
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders (2019) — 403 citations
- SUPERB: Speech processing Universal PERformance Benchmark (2021) — 1,225 citations
- SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities (2022) — 133 citations
- SpeechNet: A Universal Modularized Model for Speech Processing Tasks (2021) — 19 citations