Ju Sun
Computational Mechanics · 2009–2018
A researcher in the Science corpus: 5 papers; trusts 103 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 68 citations into it; #2,702 of 10,001 by trust here, #1,190 by citations
- Computer Vision and Pattern Recognition — 65 citations into it; #6,256 of 21,575 by trust here, #4,105 by citations
- Artificial Intelligence — 33 citations into it; #11,060 of 35,345 by trust here, #6,956 by citations
- Optimization & Training — 28 citations into it
- Signal Processing — 25 citations into it; #6,324 of 7,572 by trust here, #4,900 by citations
- Numerical Analysis — 17 citations into it
- Statistics and Probability — 16 citations into it
- Radiation — 13 citations into it; #117 of 407 by trust here, #103 by citations
Whom Ju Sun trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- E.J. Candes
- David G. Lowe
- Praneeth Netrapalli
- Moritz Hardt
- Sanjeev Arora
- Pierre-Antoine Absil
- Prateek Jain
- Rong Ge
- Geoffrey E. Hinton
- Alekh Agarwal
Who trusts Ju Sun overall
- Samet Oymak
- Rina Panigrahy
- Jason D. Lee
- Yu-Gang Jiang
- Xiaodong Yang
- Yuejie Chi
- Lixin Duan
- Yu Kong
- Kui Liu
- Adriana Kovashka
Papers from Ju Sun's perspective
Ordered by how strongly the researchers Ju Sun 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Hierarchical spatio-temporal context modeling for action recognition (2009) — 450 citations
- Robust Recovery of Subspace Structures by Low-Rank Representation (2010) — 3,507 citations
- A Geometric Analysis of Phase Retrieval (2016) — 567 citations
- Weighted AdaGrad with Unified Momentum (2018) — 43 citations
- Complete dictionary recovery over the sphere (2015) — 198 citations