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Author

Hongfan Gao

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Book Open access Aug 2026

PolarFormer: Radial-Angular Latent Modeling for Unconditional Time Series Generation

This work proposes PolarFormer, a novel framework for time series generation that addresses limitations through a polar decomposition-based discrete representation, and proposes a structurally decoupled generation strategy that models radial and angular token sequences jointly while leveraging their orthogonality to su...

Jiahong Lyu, Hongfan Gao, Wang-Meng Shen et al. · 1 citation
Book Aug 2026

PolarFormer: Radial-Angular Latent Modeling for Unconditional Time Series Generation

Time series generation is essential for data augmentation and privacy-preserving analysis across many real-world domains. Recent progress in discrete token modeling~(DTM) has demonstrated strong potential by transforming continuous sequences into discrete representations and performing generation in the latent space. H...

Jiahong Lyu, Hongfan Gao, Wangmeng Shen et al. · 0 citations

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