171 citations · 357 across the 21 of their papers we have counts for
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stat.ML2019★ 5 cited
Kernelized Wasserstein Natural Gradient
Michael Arbel, Arthur Gretton, Wuchen Li +1
Many machine learning problems can be expressed as the optimization of some cost functional over a parametric family of probability distributions. It is often beneficial to solve s…
stat.ML2019★ 51 cited
Maximum Mean Discrepancy Gradient Flow
Michael Arbel, Anna Korba, Adil Salim +1
We construct a Wasserstein gradient flow of the maximum mean discrepancy (MMD) and study its convergence properties. The MMD is an integral probability metric defined for a reprodu…