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Probabilistic numerics
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<p>Probabilistic numerics is an <a href="https://www.probabilistic-numerics.org">active</a> field of study at the intersection of <a href="/facts/Applied_mathematics/qyqklXXm">applied mathematics</a>, <a href="/facts/Statistics/DNPsKGYU">statistics</a>, and <a href="/facts/Machine_learning/e0w0XJTu">machine learning</a> centering on the concept of uncertainty in <a href="/facts/Computation/qLsELosq">computation</a>. In probabilistic numerics, tasks in <a href="/facts/Numerical_analysis/QT9cYa9z">numerical analysis</a> such as finding numerical solutions for <a href="/facts/Numerical_integration/MwJnvcDV">integration</a>, <a href="/facts/Numerical_linear_algebra/jnS6Tteb">linear algebra</a>, <a href="/facts/Numerical_optimisation/oRn8Iv5I">optimization</a> and <a href="/facts/Computer_simulation/Re6o8vzN">simulation and differential equations</a> are seen as problems of statistical, probabilistic, or <a href="/facts/Bayesian_inference/tEpK3zLx">Bayesian inference</a>. </p>