Lu Liu

Artificial Intelligence · with Tan · 2019

A researcher in the Science corpus: 2 papers; trusts 170 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it
• Computer Vision and Pattern Recognition — 34 citations into it
• Representation & Self-Supervised Learning — 30 citations into it; #2,361 of 3,145 by trust here, #3,089 by citations
• Optimization & Training — 13 citations into it
• Probabilistic & Bayesian Methods — 11 citations into it
• Natural Language Processing — 8 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Model Architectures — 5 citations into it

Whom Lu Liu trusts overall

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

1. Radford M. Neal
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Yarin Gal
5. Alex Krizhevsky
6. Diederik P. Kingma
7. Kaiming He
8. Yann LeCun
9. Ilya Sutskever
10. Thorsten Joachims

Who trusts Lu Liu overall

1. Eric Arazo
2. Antoine Saporta
3. Andrew Tao
4. Diego Ortego
5. Paul Albert
6. Tuan-Hung Vu
7. Karan Sapra
8. Qizhe Xie
9. Noel Edward O'Connor
10. Matthieu Cord

Papers from Lu Liu's perspective

Ordered by how strongly the researchers Lu 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Decoupled Certainty-Driven Consistency Loss for Semi-supervised Learning (2019) — 19 citations
• Certainty-Driven Consistency Loss for Semi-supervised Learning (2019) — 13 citations