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Aug 2026
PatchCLE: Breaking the Linear Representation Bottleneck in Time Series Forecasting via Soft Contrastive Learning
A novel representation-enhanced forecasting model, termed PatchCLE (Patch Contrastive Learning Encoder), is proposed, which innovatively integrates soft contrastive learning into multivariate time series forecasting in order to improve representation quality and resolve the computational complexity challenges associate...
Meng-Sen Wu, Haochen Shi, Sheng-Dong Du et al.
· Proceedings of the 32nd ACM... · 0 citations