BROJA-2PID: A robust estimator for bivariate partial information decomposition
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Abstract (arXiv)
Makkeh, Theis, and Vicente found in [8] that Cone Programming model is the most robust to compute the Bertschinger et al. partial information decompostion (BROJA PID) measure [1]. We developed a production-quality robust software that computes the BROJA PID measure based on the Cone Programming model. In this paper, we prove the important property of strong duality for the Cone Program and prove an equivalence between the Cone Program and the original Convex problem. Then describe in detail our software and how to use it.newlineindent
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Feb 2018.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 2; 2025: 1.
6 papers.
- 2023Quantifying & Modeling Multimodal Interactions: An Information Decomposition Frameworkcited by 81
- 2021A Rigorous Information-Theoretic Definition of Redundancy and Relevancy in Feature Selection Based on (Partial) Information Decompositioncited by 25
- 2025A Generalized Information Bottleneck Theory of Deep Learningcited by 4
- 2024Partial Information Decomposition for Data Interpretability and Feature Selectioncited by 3
- 2024Dissipation alters modes of information encoding in small quantum reservoirs near criticalitycited by 3
- 2021Interaction-Aware Sensitivity Analysis for Aerodynamic Optimization Results using Information Theorycited by 0
- 2025A Generalized Information Bottleneck Theory of Deep Learning30 Sep 2025
- 2024Dissipation alters modes of information encoding in small quantum reservoirs near criticality24 Dec 2024
- 2024Partial Information Decomposition for Data Interpretability and Feature Selection29 May 2024
- 2023Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework23 Feb 2023
- 2021Interaction-Aware Sensitivity Analysis for Aerodynamic Optimization Results using Information Theory10 Dec 2021
- 2021A Rigorous Information-Theoretic Definition of Redundancy and Relevancy in Feature Selection Based on (Partial) Information Decomposition10 May 2021