Diffusion model for relational inference

• URL: http://arxiv.org/abs/2401.16755v2
• Date: Thu, 20 Jun 2024 13:19:23 GMT
• Title: Diffusion model for relational inference
• Authors: Shuhan Zheng, Ziqiang Li, Kantaro Fujiwara, Gouhei Tanaka,
• Abstract summary: We propose a financial price model for systems with observable dynamics. DiffRI learns to infer the probability of presence of connections between components through conditional diffusion modeling.
• Score: 2.83334745695045
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Dynamical behaviors of complex interacting systems, including brain activities, financial price movements, and physical collective phenomena, are associated with underlying interactions between the system's components. The issue of uncovering interaction relations in such systems using observable dynamics is called relational inference. In this study, we propose a Diffusion model for Relational Inference (DiffRI), inspired by a self-supervised method for probabilistic time series imputation. DiffRI learns to infer the probability of the presence of connections between components through conditional diffusion modeling.

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