Kurt Geihs

Artificial Intelligence · 2009–2019

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it
• Reinforcement Learning — 12 citations into it

Whom Kurt Geihs trusts overall

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

1. Sepp Hochreiter
2. Stefan Schaal
3. Peng Peng
4. M. Mohan
5. Sainbayar Sukhbaatar

Papers from Kurt Geihs's perspective

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

1. Long Short-Term Memory
2. Human-level control through deep reinforcement learning
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Mastering the game of Go with deep neural networks and tree search
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• When Does Communication Learning Need Hierarchical Multi-Agent Deep Reinforcement Learning (2019) — 6 citations
• Software Engineering for Self-Adaptive Systems: A Second Research Roadmap (2010) — 858 citations
• Software Engineering for Self-Adaptive Systems: A Research Roadmap (2009) — 1,243 citations