Anne-Marie Rickmann

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Meta & Continual Learning — 8 citations into it

Whom Anne-Marie Rickmann trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Yoshua Bengio
5. Ian J. Goodfellow
6. Yann LeCun
7. Nitish Srivastava
8. David Lopez-Paz
9. Diederik P. Kingma
10. Marc'Aurelio Ranzato

Papers from Anne-Marie Rickmann's perspective

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

Their papers

• Importance Driven Continual Learning for Segmentation Across Domains (2020) — 36 citations