Karin Stacke

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 45 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 35 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Safety, Robustness & Interpretability — 13 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Karin Stacke trusts overall

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

1. Christian Szegedy
2. Kaiming He
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Deborah Silver
7. Yann LeCun
8. Diederik P. Kingma
9. Ilya Sutskever
10. Dumitru Erhan

Papers from Karin Stacke's perspective

Ordered by how strongly the researchers Karin Stacke 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. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Measuring Domain Shift for Deep Learning in Histopathology (2020) — 282 citations