Ruiqi Guo
Computer Vision and Pattern Recognition · 2011–2019
A researcher in the Science corpus: 8 papers; trusts 534 researchers and is trusted by 1,366 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 120 citations into it; #1,119 of 21,575 by trust here, #3,955 by citations
- Artificial Intelligence — 81 citations into it; #6,065 of 35,345 by trust here, #5,084 by citations
- Information Retrieval & Search — 48 citations into it; #658 of 1,022 by trust here, #602 by citations
- Representation & Self-Supervised Learning — 20 citations into it
- Aerospace Engineering — 19 citations into it
- Media Technology — 16 citations into it
- Signal Processing — 16 citations into it
- Efficiency & Compression — 9 citations into it; #1,033 of 1,264 by trust here, #731 by citations
Whom Ruiqi Guo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- David G. Lowe
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Artem Babenko
- Ilya Sutskever
- Herv'e J'egou
Who trusts Ruiqi Guo overall
- Saurabh Gupta
- Michael Firman
- Abhinav Kumar Gupta
- X. Wang
- Luyu Gao
- Ross B. Girshick
- Shuran Song
- Jitendra Malik
- Pablo Arbeláez
- D. Gillick
Papers from Ruiqi Guo's perspective
Ordered by how strongly the researchers Ruiqi Guo 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Multi-scale Orderless Pooling of Deep Convolutional Activation Features (2014) — 1,117 citations
- Support Surface Prediction in Indoor Scenes (2013) — 94 citations
- Efficient Natural Language Response Suggestion for Smart Reply (2017) — 514 citations
- Quantization based Fast Inner Product Search (2015) — 117 citations
- Single-image shadow detection and removal using paired regions (2011) — 343 citations
- Accelerating Large-Scale Inference with Anisotropic Vector Quantization (2019) — 574 citations
- Optimal Noise-Adding Mechanism in Additive Differential Privacy (2018) — 36 citations
- Multiscale Quantization for Fast Similarity Search (2017) — 80 citations