A weighted l1-regularized estimator for high-dimensional multivariate VAR that incorporates spatial graph constraints to recover sparse spatio-temporal transition structures.
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2 Pith papers cite this work. Polarity classification is still indexing.
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TTCD uses a non-stationary feature learner and reconstruction-guided distillation inside a transformer to infer contemporaneous and lagged causal graphs from non-stationary time series without strong noise assumptions.
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High-Dimensional Multivariate VAR Estimation with Spatio-Temporal Structure
A weighted l1-regularized estimator for high-dimensional multivariate VAR that incorporates spatial graph constraints to recover sparse spatio-temporal transition structures.
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TTCD:Transformer Integrated Temporal Causal Discovery from Non-Stationary Time Series Data
TTCD uses a non-stationary feature learner and reconstruction-guided distillation inside a transformer to infer contemporaneous and lagged causal graphs from non-stationary time series without strong noise assumptions.