2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2020★ 2 cited
Improving Fair Predictions Using Variational Inference In Causal Models
Rik Helwegen, Christos Louizos, Patrick Forré
The importance of algorithmic fairness grows with the increasing impact machine learning has on people's lives. Recent work on fairness metrics shows the need for causal reasoning…
stat.ML2019★ 1 cited
Reparameterizing Distributions on Lie Groups
Luca Falorsi, Pim de Haan, Tim R. Davidson +1
Reparameterizable densities are an important way to learn probability distributions in a deep learning setting. For many distributions it is possible to create low-variance gradien…