841 citations · 1.2k across the 34 of their papers we have counts for
Showing 2018 · stat.MLShow all
3 papers · 2 filters
stat.ML2018★ 13 cited
Neural Likelihoods via Cumulative Distribution Functions
Pawel Chilinski, Ricardo Silva
We leverage neural networks as universal approximators of monotonic functions to build a parameterization of conditional cumulative distribution functions (CDFs). By the applicatio…
stat.ML2018★ 12 cited
Causal Interventions for Fairness
Matt J. Kusner, Chris Russell, Joshua R. Loftus +1
Most approaches in algorithmic fairness constrain machine learning methods so the resulting predictions satisfy one of several intuitive notions of fairness. While this may help pr…
stat.ML2018★ 20 cited
Alpha-Beta Divergence For Variational Inference
Jean-Baptiste Regli, Ricardo Silva
This paper introduces a variational approximation framework using direct optimization of what is known as the {\it scale invariant Alpha-Beta divergence} (sAB divergence). This new…