Hao Liu

Computer Vision and Pattern Recognition · with Chen · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 231 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 89 citations into it; #20,324 of 21,575 by trust here, #7,421 by citations
• Artificial Intelligence — 58 citations into it; #33,179 of 35,345 by trust here, #10,566 by citations
• Generative Models — 46 citations into it; #1,116 of 1,956 by trust here, #711 by citations
• Natural Language Processing — 20 citations into it
• Representation & Self-Supervised Learning — 11 citations into it

Whom Hao Liu trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Diederik P. Kingma
6. Yann LeCun
7. Ilya Sutskever
8. Karen Simonyan
9. Jeff Donahue
10. Ross B. Girshick

Who trusts Hao Liu overall

1. Chunyuan Li
2. Fei Ye
3. Yunchen Pu
4. Sai Rajeswar
5. Tian Han
6. Adrian G. Bors
7. Timothée Lesort
8. Zhiqin Chen
9. Chongxuan Li
10. Mihaela Rosca

Papers from Hao Liu's perspective

Ordered by how strongly the researchers Hao Liu 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. 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

• UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning (2020) — 425 citations
• Triangle Generative Adversarial Networks (2017) — 142 citations
• ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching (2017) — 227 citations