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.
We use the first 20% of the data for tuning
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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.