3 papers
cs.LG2026
Overcoming the Modality Gap in Context-Aided Forecasting
Vincent Zhihao Zheng, Ãtienne Marcotte, Arjun Ashok +4
The paper introduces a semi‑synthetic data augmentation technique to create high‑quality contextual information for time‑series forecasting, producing a 7 million‑sample dataset (C…
cs.LG2025
Nearest Neighbor Multivariate Time Series Forecasting
Huiliang Zhang, Ping Nie, Lijun Sun +1
Multivariate time series (MTS) forecasting has a wide range of applications in both industry and academia. Recently, spatial-temporal graph neural networks (STGNNs) have gained pop…
stat.ML2025
Generalized Least Squares Kernelized Tensor Factorization
Mengying Lei, Lijun Sun
Recovering incomplete multidimensional tensor-structured data is a fundamental task in many real-world applications. Smoothness-constrained low-rank tensor factorization effectivel…