Jen-Yu Liu

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it; #24,883 of 35,345 by trust here, #34,213 by citations
• Signal Processing — 7 citations into it; #5,203 of 7,572 by trust here, #7,324 by citations
• Computer Vision and Pattern Recognition — 5 citations into it
• Model Architectures — 5 citations into it

Whom Jen-Yu Liu trusts overall

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

1. Naoya Takahashi
2. Diederik P. Kingma
3. Andrew L. Maas
4. Sergey Ioffe
5. Tim Salimans
6. Yuki Mitsufuji
7. Olaf Ronneberger
8. Antoine Liutkus
9. Aditya Arie Nugraha
10. Fabian-Robert Stöter

Who trusts Jen-Yu Liu overall

1. David Samuel
2. Aditya Ganeshan
3. Jason Naradowsky

Papers from Jen-Yu Liu's perspective

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

Their papers

• Denoising Auto-Encoder with Recurrent Skip Connections and Residual Regression for Music Source Separation (2018) — 44 citations