Zhenyu Huang

Reinforcement Learning · IEEE Transactions on Power Systems · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 8 citations into it

Whom Zhenyu Huang trusts

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

1. Stephen W. Carden (in Reinforcement Learning)

Who trusts Zhenyu Huang

1. José Antonio Lozano (in Artificial Intelligence)
2. Santiago Mazuelas (in Artificial Intelligence)
3. Verónica Álvarez (in Artificial Intelligence)

Papers from Zhenyu Huang's perspective

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

1. Human-level control through deep reinforcement learning
2. Proximal Policy Optimization Algorithms (arXiv.org)
3. Deep Reinforcement Learning that Matters
4. OpenAI Gym
5. I and J
6. and s
7. Constrained Policy Optimization
8. Learning Navigation Behaviors End-to-End With AutoRL
9. Influence of cultivation temperature on the ligninolytic activity of selected fungal strains
10. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking (IEEE Transactions on Signal Processing)

Their papers

• Adaptive Power System Emergency Control Using Deep Reinforcement Learning (2019) — 348 citations
• Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work (2019) — 526 citations
• Adaptive adjustment of noise covariance in Kalman filter for dynamic state estimation (2017) — 350 citations