Yun Bai

Water resources management · with Chen · 2014–2018

A researcher in the Science corpus: 4 papers; trusts 1 researcher and is trusted by 1 researcher here, as inferred from the citation graph.

Whom Yun Bai trusts overall

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

1. Stéphane Mallat
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Vahid Nourani

Who trusts Yun Bai overall

1. Chaopeng Shen
2. Guoqiang Chen
3. Farnaz Fotovatikhah
4. Tianyu Long

Papers from Yun Bai's perspective

Ordered by how strongly the researchers Yun Bai 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. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Learning Multiple Layers of Features from Tiny Images
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet Large Scale Visual Recognition Challenge
10. Random Forests

Their papers

• Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models (2016) — 181 citations
• Forecasting the output of shale gas in China using an unbiased grey model and weakening buffer operator (2018) — 141 citations
• Multiple Random Forests Modelling for Urban Water Consumption Forecasting (2017) — 84 citations
• A multi-scale relevance vector regression approach for daily urban water demand forecasting (2014) — 83 citations