34 citations · 55 across the 12 of their papers we have counts for
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cs.LG2020★ 9 cited
Transforming Gaussian Processes With Normalizing Flows
Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch +1
Gaussian Processes (GPs) can be used as flexible, non-parametric function priors. Inspired by the growing body of work on Normalizing Flows, we enlarge this class of priors through…
cs.LG2020★ 4 cited
On Calibration of Mixup Training for Deep Neural Networks
Juan Maroñas, Daniel Ramos, Roberto Paredes
Deep Neural Networks (DNN) represent the state of the art in many tasks. However, due to their overparameterization, their generalization capabilities are in doubt and still a fiel…