Chaopeng Shen
Artificial Intelligence · 2014–2019
A researcher in the Science corpus: 3 papers; trusts 697 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 69 citations into it
- Computer Vision and Pattern Recognition — 52 citations into it
- Environmental Engineering — 30 citations into it; #558 of 5,479 by trust here, #2,438 by citations
- Water Science and Technology — 22 citations into it; #91 of 1,711 by trust here, #820 by citations
- Global and Planetary Change — 21 citations into it; #851 of 10,225 by trust here, #5,517 by citations
- Model Architectures — 20 citations into it
- Molecular Biology — 17 citations into it
- Materials Chemistry — 16 citations into it
Whom Chaopeng Shen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Sepp Hochreiter
- Yoshua Bengio
- J. Urgen Schmidhuber
- Diederik P. Kingma
- Yann LeCun
- Alex Krizhevsky
- Matthew D. Zeiler
- Ilya Sutskever
- Ian J. Goodfellow
Who trusts Chaopeng Shen overall
- Siwei Yu
- Hristos Tyralis
- Guangtao Fu
- Jianwei Ma
- Mengyuan Zhu
- Georgia A. Papacharalampous
- Yiwen Jin
- R. Fisher
- Jiawei Wang
- Andreas Langousis
Papers from Chaopeng Shen's perspective
Ordered by how strongly the researchers Chaopeng Shen trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Enhancing Streamflow Forecast and Extracting Insights Using Long‐Short Term Memory Networks With Data Integration at Continental Scales (2019) — 403 citations
- A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists (2017) — 956 citations
- Surface‐subsurface model intercomparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks (2014) — 298 citations