FPSeq2Q: Fully Parameterized Sequence to Quantile Regression for Net-Load Forecasting With Uncertainty Estimates
Author:
Affiliation:
1. ITI, LARSyS, Técnico Lisboa, Lisbon, Portugal
Funder
Portuguese Foundation for Science and Technology
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/5165411/9761268/09701598.pdf?arnumber=9701598
Reference66 articles.
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4. How do mixture density RNNs predict the future?;ellefsen;arXiv 1901 07859,2019
5. Well-calibrated regression uncertainty in medical imaging with deep learning;laves;Proc 3rd Conf Med Imag Deep Learn,2020
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