G. Zhang

Model Architectures · with Chu · 2000–2007

A researcher in the Science corpus: 5 papers; trusts 35 researchers and is trusted by 171 researchers here, as inferred from the citation graph.

Subfields

• Model Architectures — 16 citations into it
• Statistics and Probability — 11 citations into it
• Artificial Intelligence — 9 citations into it; #1,309 of 35,345 by trust here, #4,860 by citations
• Management Science and Operations Research — 9 citations into it; #100 of 11,946 by trust here, #615 by citations
• Scaling & Learning Theory — 7 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Time-Series & Forecasting — 5 citations into it

Whom G. Zhang trusts overall

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

1. Russell Reed
2. Ed McKenzie
3. David Hilton Wolpert
4. R. Golden
5. Andrew H. Sung
6. Spyros Makridakis
7. Michael P. Perrone
8. Kurt Hornik
9. Halbert White
10. Stuart Geman

Who trusts G. Zhang overall

1. Mehdi Khashei
2. V. Ediger
3. Anastasia Borovykh
4. Lazim Abdullah
5. Durdu Ömer Faruk
6. Yuehui Chen
7. Hamid Moeeni
8. Sasan Barak
9. Jacinta Chan Phooi M’ng
10. Tanujit Chakraborty

Papers from G. Zhang's perspective

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

Their papers

• Time series forecasting using a hybrid ARIMA and neural network model (2003) — 4,188 citations
• Avoiding Pitfalls in Neural Network Research (2007) — 155 citations
• Neural networks for classification: a survey (2000) — 1,937 citations
• A simulation study of artificial neural networks for nonlinear time-series forecasting (2001) — 352 citations
• A comparative study of linear and nonlinear models for aggregate retail sales forecasting (2003) — 240 citations