40 citations · 72 across the 3 of their papers we have counts for
3 papers
astro-ph.CO2020★ 14 cited
Flow-Based Likelihoods for Non-Gaussian Inference
Ana Diaz Rivero, Cora Dvorkin
We investigate the use of data-driven likelihoods to bypass a key assumption made in many scientific analyses, which is that the true likelihood of the data is Gaussian. In particu…
astro-ph.CO2019★ 40 cited
Direct Detection of Dark Matter Substructure in Strong Lens Images with Convolutional Neural Networks
Ana Diaz Rivero, Cora Dvorkin
Strong gravitational lensing is a promising way of uncovering the nature of dark matter, by finding perturbations to images that cannot be well accounted for by modeling the lens g…
astro-ph.CO2019★ 18 cited
Observable Predictions for Massive-Neutrino Cosmologies with Model-Independent Dark Energy
Ana Diaz Rivero, V. Miranda, Cora Dvorkin
We investigate the bounds on the sum of neutrino masses in a cosmic-acceleration scenario where the equation of state of dark energy (DE) is constructed in a model-independe…