Yanfei Kang

Economics and Econometrics · 2017–2022

A researcher in the Science corpus: 4 papers; trusts 48 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Economics and Econometrics — 269 citations into it
• Management Science and Operations Research — 255 citations into it; #11,146 of 11,946 by trust here, #4,921 by citations
• Finance — 121 citations into it
• Statistics and Probability — 110 citations into it
• Artificial Intelligence — 103 citations into it
• Signal Processing — 60 citations into it; #7,178 of 7,572 by trust here, #4,051 by citations
• Time-Series & Forecasting — 54 citations into it
• Global and Planetary Change — 33 citations into it

Whom Yanfei Kang trusts overall

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

1. Rob J Hyndman
2. Spyros Makridakis
3. Vassilios Assimakopoulos
4. Kaiming He
5. George Athanasopoulos
6. Alex Graves
7. Esfandiar Maasoumi
8. Chstoph Bandt
9. Anne B. Koehler
10. Ilya Sutskever

Who trusts Yanfei Kang overall

1. Pablo Montero-Manso
2. Rob J Hyndman
3. Evangelos Spiliotis
4. Spyros Makridakis
5. George Athanasopoulos
6. Pedro Lara-Benítez

Papers from Yanfei Kang's perspective

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

Their papers

• Probabilistic Forecasting with Temporal Convolutional Neural Network (2019) — 405 citations
• Visualising forecasting algorithm performance using time series instance spaces (2017) — 174 citations
• Forecast combinations: An over 50-year review (2022) — 258 citations
• Forecasting: theory and practice (2020) — 551 citations