Liu Ren
Computer Vision and Pattern Recognition · with Xu · 2011–2020
A researcher in the Science corpus: 5 papers; trusts 238 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 75 citations into it
- Artificial Intelligence — 69 citations into it; #30,101 of 35,345 by trust here, #19,018 by citations
- Safety, Robustness & Interpretability — 22 citations into it; #1,909 of 2,251 by trust here, #2,014 by citations
- Signal Processing — 13 citations into it
- Natural Language Processing — 10 citations into it
- Biophysics — 7 citations into it
Whom Liu Ren trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Sergey Ioffe
- Yoshua Bengio
- Kaiming He
- David G. Lowe
- Ilya Sutskever
- Yann LeCun
- Andrea Vedaldi
- Diederik P. Kingma
Who trusts Liu Ren overall
Papers from Liu Ren's perspective
Ordered by how strongly the researchers Liu Ren trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Going deeper with convolutions
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Accurate 3D pose estimation from a single depth image (2011) — 272 citations
- Improve Unsupervised Domain Adaptation with Mixup Training (2020) — 275 citations
- Interpretable and Steerable Sequence Learning via Prototypes (2019) — 168 citations
- Sequence Synopsis: Optimize Visual Summary of Temporal Event Data (2018) — 105 citations
- Do Convolutional Neural Networks Learn Class Hierarchy? (2017) — 232 citations