11 citations · 11 across the 4 of their papers we have counts for
4 papers
HyFAD: Hybrid Time-Frequency Diffusion with Frequency-Aware Embedding for Time Series Imputation
Hongfan Gao, Wangmeng Shen, Bin Yang +1
Diffusion models have demonstrated strong performance in time series modeling due to their ability to progressively capture complex data distributions through iterative denoising.…
VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
Xingjian Wu, Xiangfei Qiu, Hongfan Gao +3
Probabilistic Time Series Forecasting (PTSF) plays a crucial role in decision-making across various fields, including economics, energy, and transportation. Most existing methods e…
MM-Path: Multi-modal, Multi-granularity Path Representation Learning -- Extended Version
Ronghui Xu, Hanyin Cheng, Chenjuan Guo +4
Developing effective path representations has become increasingly essential across various fields within intelligent transportation. Although pre-trained path representation learni…
SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
Hongfan Gao, Wangmeng Shen, Xiangfei Qiu +3
Probabilistic time series imputation has been widely applied in real-world scenarios due to its ability for uncertainty estimation and denoising diffusion probabilistic models~(DDP…