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Found 5 papers, 2 papers with code
An Early Fault Detection Method of Rotating Machines Based on Multiple Feature Fusion with Stacking Architecture
One of the key points of EFD is developing a generic model to extract robust and discriminative features from different equipment for early fault detection.
Meta-Learning Based Early Fault Detection for Rolling Bearings via Few-Shot Anomaly Detection
To address this problem, many transfer learning based EFD methods utilize historical data to learn transferable domain knowledge and conduct early fault detection on new target bearings.
M2N: Mesh Movement Networks for PDE Solvers
However, mesh movement methods, such as the Monge-Ampere method, require the solution of auxiliary equations, which can be extremely expensive especially when the mesh is adapted frequently.
Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks
This paper presents a problem in power networks that creates an exciting and yet challenging real-world scenario for application of multi-agent reinforcement learning (MARL).
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Learning to Shape Rewards using a Game of Two Partners
Reward shaping (RS) is a powerful method in reinforcement learning (RL) for overcoming the problem of sparse or uninformative rewards.
