Yixin Liu

Artificial Intelligence · with Pan · 2021–2022

A researcher in the Science corpus: 3 papers; trusts 89 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 145 citations into it
• Graph Learning — 52 citations into it
• Representation & Self-Supervised Learning — 46 citations into it
• Computer Vision and Pattern Recognition — 45 citations into it
• Statistical and Nonlinear Physics — 43 citations into it
• Information Systems — 37 citations into it
• Molecular Biology — 27 citations into it
• Generative Models — 5 citations into it

Whom Yixin Liu trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Kaiming He
4. Yoshua Bengio
5. Alex Krizhevsky
6. Thomas Kipf
7. Max Welling
8. Yann LeCun
9. Ilya Sutskever
10. Tomas Mikolov

Who trusts Yixin Liu overall

1. Yaochen Xie
2. Yue Tan
3. Ming Jin

Papers from Yixin Liu's perspective

Ordered by how strongly the researchers Yixin Liu 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Graph Neural Networks for Graphs With Heterophily: A Survey (2022) — 315 citations
• Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning (2021) — 488 citations
• Graph Self-Supervised Learning: A Survey (2021) — 758 citations