Rae Jeong

Reinforcement Learning · 2019

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 97 citations into it
• Artificial Intelligence — 89 citations into it

Whom Rae Jeong trusts overall

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

1. Sergey Levine

Papers from Rae Jeong's perspective

Ordered by how strongly the researchers Rae Jeong 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. ImageNet Large Scale Visual Recognition Challenge
4. Human-level control through deep reinforcement learning
5. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
6. Layer Normalization
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Long Short-Term Memory
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Scaling data-driven robotics with reward sketching and batch reinforcement learning (2019) — 160 citations
• A Framework for Data-Driven Robotics (2019) — 30 citations