FINDING COHERENT INFERENCES ACROSS DOMAINS
    1.
    发明公开

    公开(公告)号:US20240143929A1

    公开(公告)日:2024-05-02

    申请号:US17977681

    申请日:2022-10-31

    CPC classification number: G06F40/30 G06F8/436 G06N20/00

    Abstract: Disclosed implementations relate to using mutual constraint satisfaction to sample from different stochastic processes and identify coherent inferences across domains. In some implementations, a first domain representation of a semantic concept may be used to conditionally sample a first set of candidate second domain representations of the semantic concept from a first stochastic process. Based on second domain representation(s) of the first set, candidate third domain representations of the semantic concept may be conditionally sampled from a second stochastic process. Based on candidate third domain representation(s), a second set of candidate second domain representations of the semantic concept may be conditionally sampled from a third stochastic process. Pairs of candidate second domain representations sampled across the first and second sets may be evaluated. Based on the evaluation, second domain representation(s) of the semantic concept are selected, e.g., as input for a downstream computer process.

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