Xilu Wang

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 37 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it
• Computational Theory and Mathematics — 48 citations into it
• Management Science and Operations Research — 30 citations into it
• Optimization & Training — 15 citations into it
• Probabilistic & Bayesian Methods — 12 citations into it
• Statistics and Probability — 11 citations into it
• Control and Systems Engineering — 5 citations into it

Whom Xilu Wang trusts overall

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

1. Kirthevasan Kandasamy
2. Neil D. Lawrence
3. James Bergstra
4. Jasper Snoek
5. Frank Hutter
6. Geoffrey E. Hinton
7. Yoshua Bengio
8. José Miguel Hernández-Lobato
9. Jonas Mockus
10. Kevin Swersky

Papers from Xilu Wang's perspective

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

Their papers

• Recent Advances in Bayesian Optimization (2022) — 580 citations