Liang Sun
Cognitive Neuroscience · with Ye · 2008–2010
A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 13 citations into it
- Artificial Intelligence — 12 citations into it; #14,710 of 35,345 by trust here, #20,836 by citations
- Computer Vision and Pattern Recognition — 9 citations into it; #9,529 of 21,575 by trust here, #13,815 by citations
- Statistics and Probability — 8 citations into it
- Molecular Biology — 6 citations into it
- Representation & Self-Supervised Learning — 5 citations into it
Whom Liang Sun trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Radford M. Neal
- Eric R. Ziegel
- J. Rodríguez
- Andre´ Elisseeff
- Yiming Yang
- Dengyong Zhou
- Deng Cai
- Sameer Agarwal
- Matthew R. Boutell
- Jason Aaron Edward Weston
Who trusts Liang Sun overall
- Min-Ling Zhang
- Farbound Tai
- Jun Yu
- Grigorios Tsoumakas
- Yanwei Fu
- Jesse Read
- Zhi-Hua Zhou
- Jiajun Bu
- Hsuan-Tien Lin
- Ioannis Manousos Katakis
Papers from Liang Sun's perspective
Ordered by how strongly the researchers Liang Sun trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Hypergraph spectral learning for multi-label classification (2008) — 297 citations
- Learning brain connectivity of Alzheimer’s disease by sparse inverse covariance estimation (2010) — 346 citations