no code implementations • 23 Feb 2022 • Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus
We propose Multivariate Quantile Function Forecaster (MQF$^2$), a global probabilistic forecasting method constructed using a multivariate quantile function and investigate its application to multi-horizon forecasting.
no code implementations • 12 Nov 2021 • Youngsuk Park, Danielle Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang
Quantile regression is an effective technique to quantify uncertainty, fit challenging underlying distributions, and often provide full probabilistic predictions through joint learnings over multiple quantile levels.
1 code implementation • 11 Dec 2020 • Kelvin Kan, James G Nagy, Lars Ruthotto
To close this gap, the hybrid method considered in our paper combines the respective strengths of the two most common forms of regularization: early stopping and weight decay.
1 code implementation • 27 May 2020 • Kelvin Kan, Samy Wu Fung, Lars Ruthotto
We present an interior point method to solve the quadratic projection problem efficiently.
Numerical Analysis Numerical Analysis