Satoshi Yagi

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #31,540 of 35,345 by trust here, #29,412 by citations
• Computer Vision and Pattern Recognition — 17 citations into it; #19,361 of 21,575 by trust here, #18,782 by citations
• Generative Models — 17 citations into it; #1,750 of 1,956 by trust here, #1,796 by citations
• Probabilistic & Bayesian Methods — 8 citations into it
• Optimization & Training — 5 citations into it

Whom Satoshi Yagi trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Danilo Jimenez Rezende
4. Yoshua Bengio
5. Max Welling
6. Alex Krizhevsky
7. Matthew D. Zeiler
8. Ruslan Salakhutdinov
9. Yann LeCun
10. J. Tomczak

Who trusts Satoshi Yagi overall

1. Arash Vahdat
2. Jan Kautz

Papers from Satoshi Yagi's perspective

Ordered by how strongly the researchers Satoshi Yagi trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. GENERATIVE ADVERSARIAL NETS
5. Gradient-based learning applied to document recognition
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. Dropout: a simple way to prevent neural networks from overfitting
10. ImageNet: A large-scale hierarchical image database

Their papers

• Variational Autoencoder with Implicit Optimal Priors (2018) — 70 citations