Fig. 4: Loss PPF for different models.
From: Selecting fitted models under epistemic uncertainty using a stochastic process on quantile functions
Each column corresponds to a different model. The PPF (percent point function; bottom row) is the inverse of the CDF (cumulative density function; top row). For calculations we interpolate 210 = 1024 points (cyan line) to obtain a smooth function; for illustration purposes here only 30 points are shown. The data for the first two columns were generated with the neuron model described at the top of our Results, where the additive noise follows either a Gaussian or Cauchy distribution. The black body radiation data for the third column were generated from a Poisson distribution using equation (38) with s = 214 and λ in the range 6μm to 20μm. Here the true noise is binomial, but the loss assumes a Gaussian. The fourth column shows an example where the data are high-dimensional; the same 30 dimensional, unit variance, isotropic Gaussian is used for both generating the data and evaluating the loss. In all panels the loss function used is the log likelihood under the model.
