Goldie Nejat

Reinforcement Learning · 2013–2019

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

• Reinforcement Learning — 10 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Artificial Intelligence — 7 citations into it
• Aerospace Engineering — 5 citations into it

Whom Goldie Nejat trusts overall

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

1. Brian Yamauchi
2. Lei Tai

Papers from Goldie Nejat's perspective

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

1. Human-level control through deep reinforcement learning
2. Asynchronous Methods for Deep Reinforcement Learning
3. ImageNet classification with deep convolutional neural networks
4. Reinforcement learning in robotics: A survey
5. Deep Recurrent Q-Learning for Partially Observable MDPs
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning
10. Long Short-Term Memory

Their papers

• Deep Reinforcement Learning Robot for Search and Rescue Applications: Exploration in Unknown Cluttered Environments (2019) — 362 citations
• Robotic Urban Search and Rescue: A Survey from the Control Perspective (2013) — 294 citations