Lorenz Wellhausen

Biomedical Engineering · 2019–2022

A researcher in the Science corpus: 3 papers; trusts 38 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Biomedical Engineering — 43 citations into it; #4,668 of 10,734 by trust here, #4,948 by citations
• Artificial Intelligence — 37 citations into it
• Control and Systems Engineering — 25 citations into it
• Computer Vision and Pattern Recognition — 24 citations into it
• Reinforcement Learning — 14 citations into it
• Aerospace Engineering — 12 citations into it; #3,315 of 6,421 by trust here, #2,086 by citations
• Optimization & Training — 8 citations into it
• Model Architectures — 6 citations into it

Whom Lorenz Wellhausen trusts overall

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

1. Jemin Hwangbo
2. Marco Hutter
3. Alex Kendall
4. Geoffrey E. Hinton
5. Ronald J. Williams
6. Yoshua Bengio
7. Diederik P. Kingma
8. Karen Simonyan
9. Alex Krizhevsky
10. Xue Bin Peng

Who trusts Lorenz Wellhausen overall

1. Zipeng Fu
2. Ashish Kumar
3. Philipp Wu
4. Ananye Agarwal
5. Ziwen Zhuang
6. Takahiro Miki

Papers from Lorenz Wellhausen's perspective

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

Their papers

• Learning robust perceptive locomotion for quadrupedal robots in the wild (2022) — 1,117 citations
• Learning quadrupedal locomotion over challenging terrain (2020) — 1,689 citations
• Where Should I Walk? Predicting Terrain Properties From Images Via Self-Supervised Learning (2019) — 212 citations