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Divide and conquer for causal computation

delete2025-07-05
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OA
AI
A
Anna Rodum Bjøru
R
Rafael Cabañas
H
Helge Langseth
A
Antonio Salmerón
DOI:10.1016/j.ijar.2025.109520delete
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Abstract

Abstract

En 中文
• Efficient causal inference in partially specified SCMs. • Theoretical proofs of correctness. • Experimental results showing efficiency of our new approach.
Keywords:
Structural causal models
Causality
Counterfactual reasoning
Satisfiability
Heuristic search

Journal

International Journal of Approximate Reasoning cover
International Journal of Approximate Reasoning
IF:
3
Papers:
3.0K
Citations:
5.1K

Organization

No organization information available
Cited Papers

Cited Papers

Credal networks
err2000-07-01
err247
PREAI
errCozman, FG
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A General Method for Deriving Tight Symbolic Bounds on Causal Effects
err2022-05-23
err0
errOAAI
errMichael C. Sachs; Gustav Jonzon; Arvid Sjölander; Erin E. Gabriel
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Efficient computation of counterfactual bounds
err2024-08-01
err1
errOAAI
errZaffalon, Marco; Antonucci, Alessandro; Cabanas, Rafael; Huber, David; Azzimonti, Dario
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