DCIts is a convolutional model whose per-sample transition tensor recovers signed, lag-resolved causal coefficients matching the ground-truth generators of eight synthetic multivariate time series.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Interpretable deep convolutional model for nonlinear multivariate time series in complex systems
DCIts is a convolutional model whose per-sample transition tensor recovers signed, lag-resolved causal coefficients matching the ground-truth generators of eight synthetic multivariate time series.