Yujia Bao
Artificial Intelligence · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 72 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 52 citations into it; #30,435 of 35,345 by trust here, #17,110 by citations
- Natural Language Processing — 39 citations into it
- Computer Vision and Pattern Recognition — 23 citations into it
- Representation & Self-Supervised Learning — 20 citations into it
- Model Architectures — 10 citations into it; #1,941 of 2,278 by trust here, #1,794 by citations
- Optimization & Training — 6 citations into it
Whom Yujia Bao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Yoon Kim
- Ilya Sutskever
- Sepp Hochreiter
- Yann LeCun
- Tomas Mikolov
- Kaiming He
Who trusts Yujia Bao overall
- Alon Jacovi
- Shiyu Chang
- Timothy M. Hospedales
- Jonathan Bragg
- Danish Pruthi
- Ningyu Zhang
- Yoav Goldberg
- Sarah Wiegreffe
- Arman Cohan
- Antreas Antoniou
Papers from Yujia Bao's perspective
Ordered by how strongly the researchers Yujia Bao 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
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Few-shot Text Classification with Distributional Signatures (2019) — 184 citations
- Deriving Machine Attention from Human Rationales (2018) — 113 citations