Qingxuan Jiang

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it

Whom Qingxuan Jiang trusts overall

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

1. John M. Lee
2. Maximilian Nickel
3. Hermann Karcher

Papers from Qingxuan Jiang's perspective

Ordered by how strongly the researchers Qingxuan Jiang 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. On the difficulty of training recurrent neural networks
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Differentiating through the Fréchet Mean (2020) — 87 citations