ADAG pre-trains a linear transformer to map observed data from many related tasks directly to DAG adjacency matrices, enabling fast zero-shot causal discovery on new order-consistent or heterogeneous datasets.
Towards causal foundation model: on duality between optimal balancing and attention
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Learning Causal Graphs at Scale: A Foundation Model Approach
ADAG pre-trains a linear transformer to map observed data from many related tasks directly to DAG adjacency matrices, enabling fast zero-shot causal discovery on new order-consistent or heterogeneous datasets.