Patricia Rubisch

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 31 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 31 citations into it; #7,607 of 21,575 by trust here, #3,267 by citations

Whom Patricia Rubisch trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Leon A. Gatys
4. Karen Simonyan
5. Geoffrey E. Hinton
6. Shaoqing Ren
7. George A. Miller
8. Ilya Sutskever
9. Christian Szegedy
10. Ross B. Girshick

Who trusts Patricia Rubisch overall

1. Robert Geirhos
2. Axel Sauer
3. Evgenia Rusak
4. Raphael Gontijo Lopes
5. Robin Rombach
6. Hyunjae Lee
7. Hyeonseob Nam
8. Katherine L. Hermann
9. Dong Yin
10. Tianyuan Zhang

Papers from Patricia Rubisch's perspective

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

Their papers

• ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness (2018) — 3,222 citations