DECAT classifies multimodal representations into four diagnostic scenarios using null-referenced metrics and a rule-based procedure to detect shared biology versus confounders without knowing the confounder identity.
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A Bayesian approach with SMC inference learns discrete causal representations from heterogeneous domains, demonstrated on social survey data.
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Discrete Causal Representations from Heterogeneous Domains: A Bayesian Approach with Social Survey Applications
A Bayesian approach with SMC inference learns discrete causal representations from heterogeneous domains, demonstrated on social survey data.