Hongyu Shen
Astronomy and Astrophysics · 2017
A researcher in the Science corpus: 2 papers; trusts 58 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Astronomy and Astrophysics — 22 citations into it; #8,975 of 10,964 by trust here, #10,437 by citations
- Artificial Intelligence — 17 citations into it; #31,817 of 35,345 by trust here, #32,362 by citations
- Computer Vision and Pattern Recognition — 13 citations into it; #19,539 of 21,575 by trust here, #20,271 by citations
- Signal Processing — 7 citations into it; #6,867 of 7,572 by trust here, #6,836 by citations
- Model Architectures — 6 citations into it
- Natural Language Processing — 6 citations into it
- Representation & Self-Supervised Learning — 5 citations into it
Whom Hongyu Shen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Alex Graves
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- J. Urgen Schmidhuber
- Oriol Vinyals
- Diederik P. Kingma
Who trusts Hongyu Shen overall
Papers from Hongyu Shen's perspective
Ordered by how strongly the researchers Hongyu 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
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-encoders (2017) — 70 citations
- Glitch Classification and Clustering for LIGO with Deep Transfer Learning (2017) — 94 citations