Leon Wenliang Zhong

Representation & Self-Supervised Learning · 2012–2014

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Representation & Self-Supervised Learning — 10 citations into it
• Artificial Intelligence — 7 citations into it; #9,366 of 35,345 by trust here, #23,731 by citations
• Civil and Structural Engineering — 6 citations into it
• Computational Mechanics — 5 citations into it; #2,151 of 10,001 by trust here, #5,813 by citations

Whom Leon Wenliang Zhong trusts overall

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

1. Theodoros Evgeniou
2. Yurii E. Nesterov
3. Jianhui Chen
4. Francis R. Bach
5. Massimiliano Pontil
6. Bart J. Bakker
7. Robert Tibshirani
8. Yu Zhang
9. Andreas Argyriou
10. Laurent Jacob

Who trusts Leon Wenliang Zhong overall

1. Mohammad Rostami
2. Lei Han
3. Yu Zhang
4. Carlo Ciliberto
5. David Isele
6. José G. C. de Souza
7. Yu Zhang
8. Qiang Yang
9. Lorenzo Rosasco
10. Matteo Negri

Papers from Leon Wenliang Zhong's perspective

Ordered by how strongly the researchers Leon Wenliang Zhong trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Topology optimization based on moving deformable components: A new computational framework (2014) — 744 citations
• Convex Multitask Learning with Flexible Task Clusters (2012) — 69 citations