Gang Fu

Artificial Intelligence · with Wang · 2017

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it; #31,082 of 35,345 by trust here, #15,004 by citations
• Computer Vision and Pattern Recognition — 5 citations into it; #19,115 of 21,575 by trust here, #10,154 by citations
• Information Systems — 5 citations into it

Whom Gang Fu trusts overall

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

1. Diederik P. Kingma
2. Sergey Ioffe

Who trusts Gang Fu overall

1. Justin Engelmann

Papers from Gang Fu's perspective

Ordered by how strongly the researchers Gang Fu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. ImageNet classification with deep convolutional neural networks
5. Factorization Machines
6. Gradient-based learning applied to document recognition
7. Residual Networks Behave Like Ensembles of Relatively Shallow Networks
8. Factorization Machines with libFM
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Polynomials with Neural Networks

Their papers

• Deep & Cross Network for Ad Click Predictions (2017) — 1,535 citations