Maike Rees

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 92 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it; #31,139 of 35,345 by trust here, #33,294 by citations
• Computer Vision and Pattern Recognition — 38 citations into it; #19,148 of 21,575 by trust here, #20,756 by citations
• Safety, Robustness & Interpretability — 14 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Model Architectures — 11 citations into it
• Optimization & Training — 9 citations into it
• Signal Processing — 6 citations into it

Whom Maike Rees trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yann LeCun
4. Kaiming He
5. Alex Krizhevsky
6. Yoshua Bengio
7. Christian Szegedy
8. Ilya Sutskever
9. Jimmy Ba
10. Sergey Ioffe

Who trusts Maike Rees overall

1. Kuilin Chen

Papers from Maike Rees's perspective

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

Their papers

• Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components (2019) — 28 citations
• Prototype-based Neural Network Layers: Incorporating Vector Quantization (2018) — 15 citations