activity
20222026
most citedDeep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions

49 citations · 84 across the 9 of their papers we have counts for

collaborators
Showing 2026Show all

1 paper · 1 filter

cs.LG2026

A Hybrid Intelligent Framework for Uncertainty-Aware Condition Monitoring of Industrial Systems

Maryam Ahang, Todd Charter, Masoud Jalayer +1

Hybrid approaches that combine data-driven learning with physics-based insight have shown promise for improving the reliability of industrial condition monitoring. This work develo…