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cs.LG2026
Extending confidence calibration to generalised measures of variation
Andrew Thompson, Vivek Desai
We propose the Variation Calibration Error (VCE) metric for assessing the calibration of machine learning classifiers. The metric can be viewed as an extension of the well-known Ex…
cs.LG2026
Uncertainty propagation through trained multi-layer perceptrons: Exact analytical results
Andrew Thompson, Miles McCrory
We give analytical results for propagation of uncertainty through trained multi-layer perceptrons (MLPs) with a single hidden layer and ReLU activation functions. More precisely, w…
math.ST2026
A Langevin sampler for quantum tomography
Tameem Adel, Abhishek Agarwal, Stéphane Chrétien +4
Quantum tomography involves obtaining a full classical description of a prepared quantum state from experimental results. We propose a Langevin sampler for quantum tomography, that…