Liang Song

Computer Vision and Pattern Recognition · with Liu · 2019

A researcher in the Science corpus: 2 papers; trusts 375 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 51 citations into it
• Artificial Intelligence — 38 citations into it
• Representation & Self-Supervised Learning — 19 citations into it
• Model Architectures — 15 citations into it
• Optimization & Training — 9 citations into it
• Meta & Continual Learning — 8 citations into it

Whom Liang Song trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Yann LeCun
4. Ross B. Girshick
5. Karen Simonyan
6. Alex Krizhevsky
7. Yoshua Bengio
8. Oriol Vinyals
9. Diederik P. Kingma
10. Sergey Ioffe

Who trusts Liang Song overall

1. Micah Goldblum

Papers from Liang Song's perspective

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

Their papers

• Fast and Generalized Adaptation for Few-Shot Learning (2019) — 8 citations
• Generalized Adaptation for Few-Shot Learning (2019) — 6 citations