176 citations · 201 across the 11 of their papers we have counts for
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stat.ML2021
Global sensitivity analysis in probabilistic graphical models
Rafael Ballester-Ripoll, Manuele Leonelli
We show how to apply Sobol's method of global sensitivity analysis to measure the influence exerted by a set of nodes' evidence on a quantity of interest expressed by a Bayesian ne…
cs.CV2021
Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation
Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll +3
We propose an end-to-end trainable framework that processes large-scale visual data tensors by looking at a fraction of their entries only. Our method combines a neural network enc…