Ke Bai

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 48 citations into it
• Computer Vision and Pattern Recognition — 41 citations into it
• Generative Models — 38 citations into it
• Probabilistic & Bayesian Methods — 36 citations into it
• Statistics and Probability — 20 citations into it

Whom Ke Bai trusts overall

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

1. Radford M. Neal
2. Diederik P. Kingma
3. Max Welling
4. Geoffrey E. Hinton
5. Tom Minka
6. Yoshua Bengio
7. Individualized Treat
8. Alex Krizhevsky
9. Aapo Hyvärinen
10. Yann LeCun

Papers from Ke Bai's perspective

Ordered by how strongly the researchers Ke Bai 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. Attention is All you Need (Neural Information Processing Systems)
6. GENERATIVE ADVERSARIAL NETS
7. Long Short-Term Memory
8. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Adversarial Learning of a Sampler Based on an Unnormalized Distribution (2019) — 10 citations
• On Fenchel Mini-Max Learning (2019) — 16 citations