Katharina Rombach

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it
• Computer Vision and Pattern Recognition — 40 citations into it

Whom Katharina Rombach trusts overall

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

1. Bernhard Schölkopf
2. Matthias Feurer
3. Geoffrey E. Hinton
4. Wolfgang Banzhaf
5. Alex Krizhevsky
6. Kevin G. Jamieson
7. Yoshua Bengio
8. Barret Zoph
9. Frank Hutter
10. Kaiming He

Papers from Katharina Rombach's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Going deeper with convolutions
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. ImageNet Large Scale Visual Recognition Challenge
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Learning Multiple Layers of Features from Tiny Images
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Automated Machine Learning in Practice: State of the Art and Recent Results (2019) — 76 citations
• Deep Learning in the Wild (2018) — 45 citations