Stefan Doerr

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Stefan Doerr trusts overall

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

1. Diederik P. Kingma
2. Alexander S. Rose
3. Karen Simonyan
4. Dorin Comaniciu
5. Gregory R. Bowman
6. K. Lindorff‐Larsen
7. M. Harvey
8. Jimmy Ba
9. Andrew Zisserman

Who trusts Stefan Doerr overall

1. Andreas Mardt
2. Hao Wu
3. Wei Wang
4. Kevin Kaichuang Yang
5. Frank No'e
6. Shaun M. Kandathil
7. Marta M. Stepniewska-Dziubinska
8. Christoph Wehmeyer
9. Raphael J. L. Townshend

Papers from Stefan Doerr's perspective

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

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

Their papers

• DeepSite: protein‐binding site predictor using 3D‐convolutional neural networks (2017) — 650 citations
• Complete protein–protein association kinetics in atomic detail revealed by molecular dynamics simulations and Markov modelling (2017) — 317 citations
• HTMD: High-Throughput Molecular Dynamics for Molecular Discovery. (2016) — 416 citations