368 citations · 736 across the 32 of their papers we have counts for
3 papers · 1 filter
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics
Ke Alexander Wang, Danielle Maddix, Yuyang Wang
We consider the problem of probabilistic forecasting over categories with graph structure, where the dynamics at a vertex depends on its local connectivity structure. We present GO…
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…
Domain Adaptation for Time Series Forecasting via Attention Sharing
Xiaoyong Jin, Youngsuk Park, Danielle C. Maddix +2
Recently, deep neural networks have gained increasing popularity in the field of time series forecasting. A primary reason for their success is their ability to effectively capture…