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Figure 6
The difference between the predictions and the true error values, where the underlying function is f(x) = [\sin(2\pi x/\lambda)]. Each point is obtained by averaging over 40 simulations (generating synthetic data and training the model 40 times). In (a) and (b), the triangles with error-bars are the actual errors of the convolution (a) and the underlying function (b), and the diamonds with error-bars represent the uncertainty inferred by the model using equation (19)[link]. In (c), (e), (d) and (f), diamonds, circles, squares and triangles are used respectively as the varied parameter increases in size. In (c) and (d), the measurement error ([\sigma_{y}/A_{y}]) is inferred from the data, whereas in (e) and (f) it is input as prior knowledge.

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