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cs.LG2025
An Empirical Bayes Analysis of Object Trajectory Representation Models
Yue Yao, Daniel Goehring, Joerg Reichardt
Linear trajectory models provide mathematical advantages to autonomous driving applications such as motion prediction. However, linear models' expressive power and bias for real-wo…
cs.LG2025
Beyond In-Distribution Performance: A Cross-Dataset Study of Trajectory Prediction Robustness
Yue Yao, Daniel Goehring, Joerg Reichardt
We study the Out-of-Distribution (OoD) generalization ability of three SotA trajectory prediction models with comparable In-Distribution (ID) performance but different model design…
cs.LG2025
Improving Out-of-Distribution Generalization of Trajectory Prediction for Autonomous Driving via Polynomial Representations
Yue Yao, Shengchao Yan, Daniel Goehring +2
Robustness against Out-of-Distribution (OoD) samples is a key performance indicator of a trajectory prediction model. However, the development and ranking of state-of-the-art (SotA…