CausalCompass benchmarks TSCD methods across eight misspecification scenarios and finds deep learning approaches generally outperform others, with no single method dominating all cases.
Neural granger causality
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Mask2Cause recovers causal graphs directly during time-series forecasting via adjacency-constrained masked attention and achieves state-of-the-art discovery performance with over 70% reduction in forecasting parameters on average.
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CausalCompass: Evaluating the Robustness of Time-Series Causal Discovery in Misspecified Scenarios
CausalCompass benchmarks TSCD methods across eight misspecification scenarios and finds deep learning approaches generally outperform others, with no single method dominating all cases.
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Mask2Cause: Causal Discovery via Adjacency Constrained Causal Attention
Mask2Cause recovers causal graphs directly during time-series forecasting via adjacency-constrained masked attention and achieves state-of-the-art discovery performance with over 70% reduction in forecasting parameters on average.