Yuxuan Liang

Artificial Intelligence · 2018–2023

A researcher in the Science corpus: 3 papers; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it
• Building and Construction — 35 citations into it
• Transportation — 29 citations into it
• Computer Vision and Pattern Recognition — 24 citations into it
• Model Architectures — 21 citations into it
• Natural Language Processing — 9 citations into it
• Management Science and Operations Research — 8 citations into it
• Optimization & Training — 5 citations into it

Whom Yuxuan Liang trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jerome H. Friedman
4. Yoshua Bengio
5. Ilya Sutskever
6. Jimmy Ba
7. Kaiming He
8. David E. Rumelhart
9. Junbo Zhang
10. Alex Krizhevsky

Who trusts Yuxuan Liang overall

1. Senzhang Wang
2. Zhongyang Han
3. Haitao Yuan
4. Jiannong Cao
5. Fuxian Li

Papers from Yuxuan Liang's perspective

Ordered by how strongly the researchers Yuxuan Liang 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. Attention is All you Need (Neural Information Processing Systems)
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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

• Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey (2023) — 520 citations
• Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning (2019) — 632 citations
• GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction (2018) — 527 citations