161 citations · 351 across the 10 of their papers we have counts for
5 papers · 1 filter
Unscented KalmanNet: Structure-Preserving Deep Learning with Calibrated Posterior Uncertainty under Incomplete Physics and Unknown Noise
Minhyeok Ko, Abdollah Shafieezadeh
Nonlinear state estimation requires sequentially fusing model-based predictions with noisy measurements. Under imperfect dynamics and unknown, time-varying noise statistics, this f…
How important are socioeconomic factors for hurricane performance of power systems? An analysis of disparities through machine learning
Alexys Herleym Rodríguez Avellaneda, Abdollah Shafieezadeh, Alper Yilmaz
This paper investigates whether socioeconomic factors are important for the hurricane performance of the electric power system in Florida. The investigation is performed using the…
Adaptive Reliability Analysis for Multi-fidelity Models using a Collective Learning Strategy
Chi Zhang, Chaolin Song, Abdollah Shafieezadeh
In many fields of science and engineering, models with different fidelities are available. Physical experiments or detailed simulations that accurately capture the behavior of the…
Adaptive network reliability analysis: Methodology and applications to power grid
Nariman L. Dehghani, Soroush Zamanian, Abdollah Shafieezadeh
Flow network models can capture the underlying physics and operational constraints of many networked systems including the power grid and transportation and water networks. However…
Lyapunov-based uncertainty-aware safe reinforcement learning
Ashkan B. Jeddi, Nariman L. Dehghani, Abdollah Shafieezadeh
Reinforcement learning (RL) has shown a promising performance in learning optimal policies for a variety of sequential decision-making tasks. However, in many real-world RL problem…