8 citations · 9 across the 4 of their papers we have counts for
4 papers
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…
A Scenario-Based Platform for Testing Autonomous Vehicle Behavior Prediction Models in Simulation
Francis Indaheng, Edward Kim, Kesav Viswanadha +4
Behavior prediction remains one of the most challenging tasks in the autonomous vehicle (AV) software stack. Forecasting the future trajectories of nearby agents plays a critical r…
A Customizable Dynamic Scenario Modeling and Data Generation Platform for Autonomous Driving
Jay Shenoy, Edward Kim, Xiangyu Yue +4
Safely interacting with humans is a significant challenge for autonomous driving. The performance of this interaction depends on machine learning-based modules of an autopilot, suc…
Optimization of Ensemble Supervised Learning Algorithms for Increased Sensitivity, Specificity, and AUC of Population-Based Colorectal Cancer Screenings
Anirudh Kamath, Aditya Singh, Raj Ramnani +2
Over 150,000 new people in the United States are diagnosed with colorectal cancer each year. Nearly a third die from it (American Cancer Society). The only approved noninvasive dia…