Q. Li

Artificial Intelligence · with Zhang · 2019

A researcher in the Science corpus: 3 papers; trusts 45 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 86 citations into it
• Computer Vision and Pattern Recognition — 65 citations into it
• Natural Language Processing — 27 citations into it
• Reinforcement Learning — 8 citations into it

Whom Q. Li trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Ronald J. Williams
6. Yann LeCun
7. Ilya Sutskever
8. Kaiming He
9. Jimmy Ba
10. Alex Graves

Papers from Q. Li's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Joint Entity Linking with Deep Reinforcement Learning (2019) — 108 citations
• Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation (2019) — 1,007 citations
• Incremental Learning from Scratch for Task-Oriented Dialogue Systems (2019) — 23 citations