Stefan Coors

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 93 citations into it
• Computational Theory and Mathematics — 35 citations into it
• Optimization & Training — 32 citations into it
• Neural Architecture Search & AutoML — 16 citations into it

Whom Stefan Coors trusts overall

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

1. Frank Hutter
2. James Bergstra
3. Jasper Snoek
4. Diederik P. Kingma

Papers from Stefan Coors's perspective

Ordered by how strongly the researchers Stefan Coors 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. ImageNet classification with deep convolutional neural networks
3. Practical Bayesian Optimization of Machine Learning Algorithms
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges (2021) — 1,013 citations
• mlr3: A modern object-oriented machine learning framework in R (2019) — 406 citations