Danielle Maddix Robinson

Danielle Maddix Robinson

Senior Applied Scientist, AWS AI Labs, PhD in Computational and Mathematical Engineering, Stanford University

Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting

Published in Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

Recommended citation: Park, Y., Maddix, D.C., Aubet, FX., Kan, K., Gasthaus, J., Wang, Y. (2022). "Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting." Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR. 151:8127-8150. https://proceedings.mlr.press/v151/park22a.html

Our Incremental Quantile Function (IQF) code is incorporated into the MQ-CNN Estimator in GluonTS.