46 citations · 177 across the 9 of their papers we have counts for
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stat.ML2019★ 21 cited
Cubic-Spline Flows
Conor Durkan, Artur Bekasov, Iain Murray +1
A normalizing flow models a complex probability density as an invertible transformation of a simple density. The invertibility means that we can evaluate densities and generate sam…
stat.ML2019★ 27 cited
Neural Spline Flows
Conor Durkan, Artur Bekasov, Iain Murray +1
A normalizing flow models a complex probability density as an invertible transformation of a simple base density. Flows based on either coupling or autoregressive transforms both o…
stat.ML2019★ 19 cited
Autoregressive Energy Machines
Charlie Nash, Conor Durkan
Neural density estimators are flexible families of parametric models which have seen widespread use in unsupervised machine learning in recent years. Maximum-likelihood training ty…