Mikhail Frank

Reinforcement Learning · 2013–2014

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 9 citations into it
• Artificial Intelligence — 7 citations into it
• Control and Systems Engineering — 6 citations into it

Whom Mikhail Frank trusts overall

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

1. J. Urgen Schmidhuber
2. Richard S. Sutton
3. Andrew Barto
4. Steven M. LaValle
5. Jan Peters
6. Stefan Schaal
7. In Proc. Icann
8. Aaron D'Souza
9. Hung Quoc Ngo
10. Sepp Hochreiter

Papers from Mikhail Frank's perspective

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

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

Their papers

• Artificial neural networks for spatial perception: Towards visual object localisation in humanoid robots (2013) — 9 citations
• Curiosity driven reinforcement learning for motion planning on humanoids (2014) — 95 citations