Guojie Song

Artificial Intelligence · Knowledge Discovery and Data Mining · 2010–2021

A researcher in the Science corpus: 9 papers; trusts 86 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 96 citations into it; #15,415 of 35,345 by trust here, #13,760 by citations
• Statistical and Nonlinear Physics — 51 citations into it; #4,758 of 10,127 by trust here, #3,513 by citations
• Representation & Self-Supervised Learning — 35 citations into it; #1,803 of 3,145 by trust here, #2,624 by citations
• Graph Learning — 34 citations into it
• Computer Vision and Pattern Recognition — 28 citations into it
• Building and Construction — 18 citations into it; #1,490 of 2,909 by trust here, #537 by citations
• Molecular Biology — 18 citations into it
• Transportation — 17 citations into it

Whom Guojie Song trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. David Kempe
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Yann LeCun
7. Ilya Sutskever
8. Kaiming He
9. Yajun Wang
10. Radford M. Neal

Who trusts Guojie Song overall

1. Yu Zhang
2. Lei Han
3. Yuchen Li
4. Matthew Veres
5. Yongxue Tian
6. Qingchen Zhang
7. Jingwen Ye
8. Xiaolei Ma
9. Qiang Yang
10. Joonhyuck Lee

Papers from Guojie Song's perspective

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

Their papers

• Influence Blocking Maximization in Social Networks under the Competitive Linear Threshold Model (2011) — 450 citations
• Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting (2021) — 738 citations
• Heterogeneous Graph Structure Learning for Graph Neural Networks (2021) — 319 citations
• Streaming Graph Neural Networks via Continual Learning (2020) — 148 citations
• Dynamic Network Embedding : An Extended Approach for Skip-gram based Network Embedding (2018) — 231 citations
• Temporal Causal Inference with Time Lag (2018) — 15 citations
• Deep Architecture for Traffic Flow Prediction: Deep Belief Networks With Multitask Learning (2014) — 1,046 citations
• Encoding Tree Sparsity in Multi-Task Learning: A Probabilistic Framework (2014) — 43 citations
• Community-based greedy algorithm for mining top-K influential nodes in mobile social networks (2010) — 583 citations