1 citations · 2 across the 9 of their papers we have counts for
7 papers
A Compression Perspective on Simplicity Bias
Tom Marty, Eric Elmoznino, Leo Gagnon +5
Deep neural networks exhibit a simplicity bias, a well-documented tendency to favor simple functions over complex ones. In this work, we cast new light on this phenomenon through t…
Machine Learning-Driven Prediction of Lithium-Ion Battery Power Capability for eVTOL Aircraft
Hao Tu, Yebin Wang, Shaoshuai Mou +1
Electric vertical take-off and landing (eVTOL) aircraft have emerged as a promising solution to transform urban transportation. They present a few technical challenges for battery…
Optimal Power Management of Battery Energy Storage Systems via Ensemble Kalman Inversion
Amir Farakhor, Iman Askari, Di Wu +1
Optimal power management of battery energy storage systems (BESS) is crucial for their safe and efficient operation. Numerical optimization techniques are frequently utilized to so…
Motion Planning for Autonomous Vehicles: When Model Predictive Control Meets Ensemble Kalman Smoothing
Iman Askari, Yebin Wang, Vedeng M. Deshpande +1
Safe and efficient motion planning is of fundamental importance for autonomous vehicles. This paper investigates motion planning based on nonlinear model predictive control (NMPC)…
Optimal Power Management for Large-Scale Battery Energy Storage Systems via Bayesian Inference
Amir Farakhor, Iman Askari, Di Wu +2
Large-scale battery energy storage systems (BESS) have found ever-increasing use across industry and society to accelerate clean energy transition and improve energy supply reliabi…
Efficient Fault Diagnosis in Lithium-Ion Battery Packs: A Structural Approach with Moving Horizon Estimation
Amir Farakhor, Di Wu, Yebin Wang +1
Safe and reliable operation of lithium-ion battery packs depends on effective fault diagnosis. However, model-based approaches often encounter two major challenges: high computatio…