Stephan Wäldchen

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 72 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it; #17,768 of 35,345 by trust here, #10,065 by citations
• Computer Vision and Pattern Recognition — 51 citations into it
• Safety, Robustness & Interpretability — 22 citations into it; #1,190 of 2,251 by trust here, #889 by citations
• Reinforcement Learning — 14 citations into it

Whom Stephan Wäldchen trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Diederik P. Kingma
5. David G. Lowe
6. Yann LeCun
7. L. Eon Bottou
8. Wojciech Samek
9. Grgoire Montavon
10. Ilya Sutskever

Who trusts Stephan Wäldchen overall

1. Wojciech Samek
2. K. Müller
3. Grgoire Montavon
4. Christopher J. Anders
5. Simon Wiedemann
6. Sebastian Lapuschkin

Papers from Stephan Wäldchen's perspective

Ordered by how strongly the researchers Stephan Wäldchen 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. 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. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Unmasking Clever Hans predictors and assessing what machines really learn (2019) — 1,223 citations