A diffusion-based framework with frequency mixup and selective consistency alignment improves cross-domain time series imputation.
IEEE Transactions on Neural Networks and Learning Systems (2021)
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Cross-Domain Conditional Diffusion Models for Time Series Imputation
A diffusion-based framework with frequency mixup and selective consistency alignment improves cross-domain time series imputation.