4 citations · 9 across the 11 of their papers we have counts for
5 papers · 1 filter
Diffusion Prior Interpolation for Flexibility Real-World Face Super-Resolution
Jiarui Yang, Tao Dai, Yufei Zhu +3
Diffusion models represent the state-of-the-art in generative modeling. Due to their high training costs, many works leverage pre-trained diffusion models' powerful representations…
TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting
Peiyuan Liu, Beiliang Wu, Yifan Hu +4
Non-stationarity poses significant challenges for multivariate time series forecasting due to the inherent short-term fluctuations and long-term trends that can lead to spurious re…
Generative Pre-Trained Diffusion Paradigm for Zero-Shot Time Series Forecasting
Jiarui Yang, Tao Dai, Naiqi Li +6
In recent years, generative pre-trained paradigms such as Large Language Models (LLMs) and Large Vision Models (LVMs) have achieved revolutionary advancements and widespread real-w…
Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting
Yifan Hu, Peiyuan Liu, Peng Zhu +2
Transformer-based and MLP-based methods have emerged as leading approaches in time series forecasting (TSF). While Transformer-based methods excel in capturing long-range dependenc…
LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling
Yaohua Zha, Naiqi Li, Yanzi Wang +6
The pre-trained point cloud model based on Masked Point Modeling (MPM) has exhibited substantial improvements across various tasks. However, these models heavily rely on the Transf…