Yu-Ho Su

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Model Architectures — 7 citations into it
• Optimization & Training — 7 citations into it

Whom Yu-Ho Su trusts overall

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

1. Alex Graves
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Alex Krizhevsky

Papers from Yu-Ho Su's perspective

Ordered by how strongly the researchers Yu-Ho Su trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Dropout: a simple way to prevent neural networks from overfitting
4. Et al
5. Generating Sequences With Recurrent Neural Networks
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Speech recognition with deep recurrent neural networks

Their papers

• EKT: Exercise-Aware Knowledge Tracing for Student Performance Prediction (2019) — 500 citations
• Finding Similar Exercises in Online Education Systems (2018) — 84 citations