1 citations · 1 across the 4 of their papers we have counts for
4 papers
Test-time GNN Model Evaluation on Dynamic Graphs
Bo Li, Xin Zheng, Ming Jin +2
Dynamic graph neural networks (DGNNs) have emerged as a leading paradigm for learning from dynamic graphs, which are commonly used to model real-world systems and applications. How…
Estimating Time Series Foundation Model Transferability via In-Context Learning
Qingren Yao, Ming Jin, Chengqi Zhang +3
Time series foundation models (TSFMs) offer strong zero-shot forecasting via large-scale pre-training, yet fine-tuning remains critical for boosting performance in domains with lim…
OASIS: Harnessing Diffusion Adversarial Network for Ocean Salinity Imputation using Sparse Drifter Trajectories
Bo Li, Yingqi Feng, Ming Jin +10
Ocean salinity plays a vital role in circulation, climate, and marine ecosystems, yet its measurement is often sparse, irregular, and noisy, especially in drifter-based datasets. T…
T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models
Yunfeng Ge, Jiawei Li, Yiji Zhao +6
Text-to-Time Series generation holds significant potential to address challenges such as data sparsity, imbalance, and limited availability of multimodal time series datasets acros…