Ke Wang

Artificial Intelligence · with Mihaylova · 2019

A researcher in the Science corpus: 1 paper; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Control and Systems Engineering — 9 citations into it
• Signal Processing — 6 citations into it
• Computational Theory and Mathematics — 5 citations into it

Whom Ke Wang trusts overall

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

1. Manfred Opper
2. Duy Nguyen-Tuong
3. Mauricio A Álvarez
4. Zoubin Ghahramani
5. Radford M. Neal
6. Matthias W. Seeger
7. Carl E. Rasmussen
8. Matthew J. Beal
9. Neil D. Lawrence
10. Phillip Boyle

Who trusts Ke Wang overall

1. Tim G. J. Rudner

Papers from Ke Wang's perspective

Ordered by how strongly the researchers Ke Wang 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. Learning Multiple Layers of Features from Tiny Images
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Online Sparse Multi-Output Gaussian Process Regression and Learning (2019) — 32 citations