5 citations · 5 across the 1 of their papers we have counts for
3 papers
cs.CV2020
Synchronizing Probability Measures on Rotations via Optimal Transport
Tolga Birdal, Michael Arbel, Umut Şimşekli +1
We introduce a new paradigm, , for synchronizing graphs with measure-valued edges. We formulate this problem as maximization of the cycle-consiste…
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
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…