11 citations · 29 across the 6 of their papers we have counts for
3 papers · 1 filter
Multivariate Quantile Function Forecaster
Kelvin Kan, François-Xavier Aubet, Tim Januschowski +4
We propose Multivariate Quantile Function Forecaster (MQF), a global probabilistic forecasting method constructed using a multivariate quantile function and investigate its app…
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting
Youngsuk Park, Danielle Maddix, François-Xavier Aubet +3
Quantile regression is an effective technique to quantify uncertainty, fit challenging underlying distributions, and often provide full probabilistic predictions through joint lear…
Avoiding The Double Descent Phenomenon of Random Feature Models Using Hybrid Regularization
Kelvin Kan, James G Nagy, Lars Ruthotto
We demonstrate the ability of hybrid regularization methods to automatically avoid the double descent phenomenon arising in the training of random feature models (RFM). The hallmar…