Quantum Entropic Causal Inference

Mohammad Ali Javidian; Vaneet Aggarwal; Fanglin Bao; Zubin Jacob

doi:10.1364/QIM.2021.F2C.3

Quantum Information and Measurement VI 2021
Technical Digest Series (Optica Publishing Group, 2021),
paper F2C.3
•https://doi.org/10.1364/QIM.2021.F2C.3

Quantum Entropic Causal Inference

Mohammad Ali Javidian, Vaneet Aggarwal, Fanglin Bao, and Zubin Jacob

Quantum Information and Measurement 2021

Washington, DC United States
1–5 November 2021
ISBN: 978-1-957171-01-2

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Quantum Information Processing and Computing III (F2C)

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M. A. Javidian, V. Aggarwal, F. Bao, and Z. Jacob, "Quantum Entropic Causal Inference," in Quantum Information and Measurement VI 2021, F. Sciarrino, N. Treps, M. Giustina, and C. Silberhorn, eds., Technical Digest Series (Optica Publishing Group, 2021), paper F2C.3.

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Abstract

Inferring causality from observational data alone is one of the most important and challenging problems in statistical inference. We propose a greedy algorithm for quantum entropic causal inference that unifies classical and quantum causal inference.

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