91 citations · 273 across the 67 of their papers we have counts for
3 papers · 2 filters
A generic physics-informed neural network-based framework for reliability assessment of multi-state systems
Taotao Zhou, Xiaoge Zhang, Enrique Lopez Droguett +1
In this paper, we leverage the recent advances in physics-informed neural network (PINN) and develop a generic PINN-based framework to assess the reliability of multi-state systems…
Synthesizing Pareto-Optimal Interpretations for Black-Box Models
Hazem Torfah, Shetal Shah, Supratik Chakraborty +2
We present a new multi-objective optimization approach for synthesizing interpretations that "explain" the behavior of black-box machine learning models. Constructing human-underst…
Scenic4RL: Programmatic Modeling and Generation of Reinforcement Learning Environments
Abdus Salam Azad, Edward Kim, Qiancheng Wu +4
The capability of a reinforcement learning (RL) agent heavily depends on the diversity of the learning scenarios generated by the environment. Generation of diverse realistic scena…