Kien Do

Representation & Self-Supervised Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 229 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Representation & Self-Supervised Learning — 23 citations into it
• Computer Vision and Pattern Recognition — 22 citations into it
• Artificial Intelligence — 17 citations into it
• Generative Models — 14 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Kien Do trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Danilo Jimenez Rezende
5. Alex Krizhevsky
6. Yann LeCun
7. Karl Ridgeway
8. J. Urgen Schmidhuber
9. Ruslan Salakhutdinov
10. Radford M. Neal

Who trusts Kien Do overall

1. Cynthia Rudin
2. Zhi Chen

Papers from Kien Do's perspective

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

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

Their papers

• Theory and Evaluation Metrics for Learning Disentangled Representations (2019) — 109 citations