Ryuki Tachibana

Reinforcement Learning · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 29 citations into it
• Artificial Intelligence — 28 citations into it

Whom Ryuki Tachibana trusts overall

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

1. Matthew D. Zeiler

Papers from Ryuki Tachibana's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. GENERATIVE ADVERSARIAL NETS
3. Asynchronous Methods for Deep Reinforcement Learning
4. Human-level control through deep reinforcement learning
5. Trust Region Policy Optimization (International Conference on Machine Learning)
6. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
7. Playing Atari with Deep Reinforcement Learning (arXiv.org)
8. ImageNet classification with deep convolutional neural networks
9. Proximal Policy Optimization Algorithms (arXiv.org)
10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers

• Constrained Exploration and Recovery from Experience Shaping (2018) — 3 citations
• Deep reinforcement learning for high precision assembly tasks (2017) — 300 citations