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New framework automates probabilistic linear solver creation

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced "affine tracing," a novel framework designed to automate the creation of probabilistic linear solvers (PLSs). This new method bridges the gap between traditional Bayesian PLSs and probabilistic iterative methods (PIMs), demonstrating that Bayesian approaches are a specific instance of affine PIMs. The affine tracing framework simplifies the implementation of these solvers by automatically constructing computational graphs from standard iterative methods, enabling more efficient uncertainty quantification in linear system solutions. AI

IMPACT Automates the construction of probabilistic solvers, potentially simplifying uncertainty quantification in machine learning and scientific computing.

RANK_REASON The cluster contains an academic paper detailing a new algorithmic framework for probabilistic linear solvers. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework automates probabilistic linear solver creation

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The cluster contains an academic paper detailing a new algorithmic framework for probabilistic linear solvers. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Jon Cockayne ·

    Affine Tracing: A New Paradigm for Probabilistic Linear Solvers

    Probabilistic linear solvers (PLSs) return probability distributions that quantify uncertainty due to limited computation in the solution of linear systems. The literature has traditionally distinguished between Bayesian PLSs, which condition a prior on information obtained from …

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