Measuring the Confidence of Traffic Forecasting Models: Techniques, Experimental Comparison and Guidelines towards Their Actionability

28 October 2022

Papers citing "Measuring the Confidence of Traffic Forecasting Models: Techniques, Experimental Comparison and Guidelines towards Their Actionability"

3 / 3 papers shown

Title
Uncertainty Quantification for Image-based Traffic Prediction across Cities Alexander Timans Nina Wiedemann Nishant Kumar Ye Hong Martin Raubal 11 1 0 11 Aug 2023
Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching Lu Zhang Wenchao Ding Jia Chen Shaojie Shen 24 36 0 05 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015