Emin Orhan

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 391 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it; #5,339 of 35,345 by trust here, #25,809 by citations
• Computer Vision and Pattern Recognition — 29 citations into it; #4,443 of 21,575 by trust here, #16,787 by citations
• Safety, Robustness & Interpretability — 18 citations into it; #649 of 2,251 by trust here, #2,110 by citations
• Model Architectures — 15 citations into it; #1,467 of 2,278 by trust here, #1,882 by citations
• Optimization & Training — 14 citations into it; #2,039 of 2,601 by trust here, #1,986 by citations
• Evaluation & Benchmarks — 7 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Emin Orhan trusts overall

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

1. Kaiming He
2. Yoshua Bengio
3. Diederik P. Kingma
4. Jonas Rauber
5. Geoffrey E. Hinton
6. Ian J. Goodfellow
7. Alex Krizhevsky
8. Wieland Brendel
9. Ross B. Girshick
10. Christian Szegedy

Who trusts Emin Orhan overall

1. Renrui Zhang
2. Marvin Zhang
3. Dan Hendrycks
4. Zhiwei Jia
5. Zeyu Han
6. Urvashi Khandelwal
7. Shuaicheng Niu
8. Sergey Levine
9. Rongyao Fang
10. Yanan Sun

Papers from Emin Orhan's perspective

Ordered by how strongly the researchers Emin Orhan 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Robustness properties of Facebook's ResNeXt WSL models (2019) — 35 citations
• A Simple Cache Model for Image Recognition (2018) — 36 citations
• Skip Connections Eliminate Singularities (2017) — 257 citations