Rosen Kralev

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 41 citations into it
• Artificial Intelligence — 37 citations into it; #35,162 of 35,345 by trust here, #25,809 by citations
• Control and Systems Engineering — 11 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it

Whom Rosen Kralev trusts overall

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

1. Chelsea Finn
2. Sergey Levine
3. Pieter Abbeel
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Yoshua Bengio
7. Richard S. Sutton
8. J. Urgen Schmidhuber
9. Ronald J. Williams
10. Alex Krizhevsky

Who trusts Rosen Kralev overall

1. Sergey Levine

Papers from Rosen Kralev's perspective

Ordered by how strongly the researchers Rosen Kralev 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Human-level control through deep reinforcement learning
9. Learning Multiple Layers of Features from Tiny Images
10. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Their papers

• Guided Meta-Policy Search (2019) — 59 citations