2019 UAI UAI 2019

Exclusivity Graph Approach to Instrumental Inequalities

Abstract

Instrumental variables allow the estimation of cause and effect relations even in presence of unobserved latent factors, thus providing a powerful tool for any science wherein causal inference plays an important role. More recently, the instrumental scenario has also attracted increasing attention in quantum physics, since it is related to the seminal Bellโ€™s theorem and in fact allows the detection of even stronger quantum effects, thus enhancing our current capabilities to process information and becoming a valuable tool in quantum cryptography. In this work, we further explore this bridge between causality and quantum theory and apply a technique, originally developed in the field of quantum foundations, to express the constraints implied by causal relations in the language of graph theory. This new approach can be applied to any causal model containing a latent variable. Here, by focusing on the instrumental scenario, it allows us to easily reproduce known results as well as obtain new ones and gain new insights on the connections and differences between the instrumental and the Bell scenarios.

๐Ÿš€ Conference Pioneer โ€” UAI 2019
๐ŸŒ‰ Interdisciplinary Bridge โ€” Artificial Intelligence and Mathematics & Optimization
๐Ÿงญ Keyword Pioneer โ€” quantum foundation
๐Ÿฃ Hot Topic Early Bird โ€” causal inference
๐Ÿ Cross-Pollinator โ€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio