Siliang Tang

Artificial Intelligence · 2015–2019

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it

Whom Siliang Tang trusts overall

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

1. Geoffrey E. Hinton

Papers from Siliang Tang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
3. Dropout: a simple way to prevent neural networks from overfitting
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Rectified Linear Units Improve Restricted Boltzmann Machines
6. GloVe: Global Vectors for Word Representation
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Gradient-based learning applied to document recognition
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Learning Dynamic Context Augmentation for Global Entity Linking (2019) — 71 citations
• Deep Compositional Cross-modal Learning to Rank via Local-Global Alignment (2015) — 52 citations