Jason Xu

Artificial Intelligence · 2014–2018

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it; #23,005 of 35,345 by trust here, #25,809 by citations
• Probabilistic & Bayesian Methods — 8 citations into it
• Statistics and Probability — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Jason Xu trusts overall

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

1. Max Welling
2. Radford M. Neal
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Steven L. Scott
6. Sylvia Frühwirth-Schnatter
7. Hugo Larochelle
8. Alex Krizhevsky
9. Michael I. Jordan
10. Diederik P. Kingma

Who trusts Jason Xu overall

1. Hermanni Hälvä
2. Stefan Falkner
3. Cheng Zhang

Papers from Jason Xu's perspective

Ordered by how strongly the researchers Jason Xu 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. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Stochastic variational inference for hidden Markov models (2014) — 99 citations
• Combination of Hyperband and Bayesian Optimization for Hyperparameter Optimization in Deep Learning (2018) — 94 citations