mlsanityData to 14 Oct 2026

Causal Inference in Network Economics

arXiv 2109.11344 ↗First posted 20 Sep 2021math.OC cs.AIcited by 3

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Abstract (arXiv)

Network economics is the study of a rich class of equilibrium problems that occur in the real world, from traffic management to supply chains and two-sided online marketplaces. In this paper we explore causal inference in network economics, building on the mathematical framework of variational inequalities, which is a generalization of classical optimization. Our framework can be viewed as a synthesis of the well-known variational inequality formalism with the broad principles of causal inference

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 3 of its 27 references that are in the map. First posted on arXiv 20 Sep 2021.

Builds on

3 of 27 references.

References · 3

  1. 2019Experimenting in Equilibriumcited by 16
  2. 2018Global Convergence to the Equilibrium of GANs using Variational Inequalitiescited by 15
  3. 2020Regularized Off-Policy TD-Learningcited by 10

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Cited by year

Citing papers per year: 2021: 1; 2022: 2.

3 papers.

  1. 2021Universal Decision Modelscited by 7
  2. 2022Unifying Causal Inference and Reinforcement Learning using Higher-Order Category Theorycited by 4
  3. 2022On The Universality of Diagrams for Causal Inference and The Causal Reproducing Propertycited by 2