Sarah Xiao

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 63 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 35 citations into it
• Artificial Intelligence — 32 citations into it
• Multimodal Learning — 14 citations into it
• Natural Language Processing — 9 citations into it
• Evaluation & Benchmarks — 6 citations into it

Whom Sarah Xiao trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Antonio Torralba
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Andrej Karpathy
6. Yoshua Bengio
7. Diederik P. Kingma
8. Ross B. Girshick
9. Li Fei-Fei
10. Ilya Sutskever

Papers from Sarah Xiao's perspective

Ordered by how strongly the researchers Sarah Xiao trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• On Modality Bias in the TVQA Dataset (2020) — 49 citations