MOSAIC recovers identifiable latent variables and their sparse associated observations in scientific time series by combining temporal causal representation learning with support recovery through a sparse additive decoder.
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MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series
MOSAIC recovers identifiable latent variables and their sparse associated observations in scientific time series by combining temporal causal representation learning with support recovery through a sparse additive decoder.