Ioannis Arapakis

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 27 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it; #30,156 of 35,345 by trust here, #19,439 by citations
• Information Systems — 13 citations into it; #7,177 of 8,771 by trust here, #3,876 by citations
• Computer Vision and Pattern Recognition — 11 citations into it; #18,514 of 21,575 by trust here, #12,992 by citations
• Model Architectures — 9 citations into it
• Management Science and Operations Research — 8 citations into it
• Generative Models — 5 citations into it
• Optimization & Training — 5 citations into it
• Recommender Systems — 5 citations into it

Whom Ioannis Arapakis trusts overall

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

1. Geoffrey E. Hinton
2. Aäron van den Oord
3. Kaiming He
4. Yoshua Bengio
5. Jimmy Ba
6. Balázs Hidasi
7. Diederik P. Kingma
8. Sergey Ioffe
9. Nal Kalchbrenner
10. Alex Krizhevsky

Who trusts Ioannis Arapakis overall

1. Fajie Yuan

Papers from Ioannis Arapakis's perspective

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

Their papers

• A Simple Convolutional Generative Network for Next Item Recommendation (2018) — 670 citations