2 papers
cs.RO2026
Designing Versatile Samples for Learned Trajectory Scoring
Yaguang Li, Jiaru Zhang, Chuheng Wei +2
Many current end-to-end driving policies emit a pool of candidate trajectories and select one, which makes selection a separable component: a scorer can be retrained while the plan…
cs.LG2026
Neural-Bayesian Structure Learning for Discrete Choice Modeling
Hyunsoo Yun, Eun Hak Lee, Jiaru Zhang +2
Conventional discrete choice and machine learning models are estimated primarily from observational data and typically treat explanatory covariates as parallel inputs, providing no…