877 citations · 1k across the 14 of their papers we have counts for
4 papers · 1 filter
TimeES: Probabilistic and Deterministic Time Series Forecasting via Evolutionary Spectra
Weiwei Ye, Renhe Jiang, Hangchen Liu +2
Real-world time series are inherently non-stationary, with trends, periodic patterns, and uncertainty evolving over time. While the Fourier domain offers a natural lens to model ti…
DiffPTS: Rethinking Diffusion ELBO for Probabilistic Time Series Forecasting
Weiwei Ye, Dongyuan Li, Hangchen Liu +3
Probabilistic time series forecasting requires modeling and predicting complex and time-varying distributions. Recently, Denoising Diffusion Probabilistic Model (DDPM)-based approa…
Explainable Hierarchical Urban Representation Learning for Commuting Flow Prediction
Mingfei Cai, Yanbo Pang, Yoshihide Sekimoto
Commuting flow prediction is an essential task for municipal operations in the real world. Previous studies have revealed that it is feasible to estimate the commuting origin-desti…
City2City: Translating Place Representations across Cities
Takahiro Yabe, Kota Tsubouchi, Toru Shimizu +2
Large mobility datasets collected from various sources have allowed us to observe, analyze, predict and solve a wide range of important urban challenges. In particular, studies hav…