5 papers
Denoising the Future: Context-Aware Spectral Diffusion for Temporal Knowledge Graph Extrapolation
Yanglei Gan, Peng He, Run Lin +3
Temporal Knowledge Graph (TKG) extrapolation seeks to infer future facts from time-varying relational histories. Recent diffusion-based approaches improve uncertainty modeling thro…
FAiT: Frequency-Aware Inverted Transformer for Multivariate Time Series Forecasting
Peng He, Yao Liu, Yanglei Gan +3
While Transformer-based architectures have established themselves as a dominant paradigm in Multivariate Time Series Forecasting (MTSF), their core self-attention mechanism inheren…
GLIDE: Graph-guided Leap Inference for Diffusion Estimation of Spatio-Temporal Point Processes
Guanyu Zhou, Yao Liu, Yanglei Gan +5
Spatio-temporal point processes (STPPs) provide a principled framework for modeling asynchronous events in continuous time and space. Recent diffusion-based approaches offer a flex…
Negative-Aware Diffusion Process for Temporal Knowledge Graph Extrapolation
Yanglei Gan, Peng He, Yuxiang Cai +3
Temporal Knowledge Graph (TKG) reasoning seeks to predict future missing facts from historical evidence. While diffusion models (DM) have recently gained attention for their abilit…
Exploiting Inter-Session Information with Frequency-enhanced Dual-Path Networks for Sequential Recommendation
Peng He, Yao Liu, Yanglei Gan +4
Sequential recommendation (SR) aims to predict a user's next item preference by modeling historical interaction sequences. Recent advances often integrate frequency-domain modules…