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20212026
most citedConvergence Rates of Gradient Methods for Convex Optimization in the Space of Measures

3 citations · 6 across the 9 of their papers we have counts for

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stat.ML2026

Quantitative Local Convergence of Mean-Field Stein Variational Gradient Flow

Lénaïc Chizat, Maria Colombo, Roberto Colombo +1

Stein Variational Gradient Descent (SVGD) is a deterministic interacting-particle method for sampling from a target probability measure given access to its score function. In the m…

math.AP2026

Quantitative Convergence of Wasserstein Gradient Flows of Kernel Mean Discrepancies

Lénaïc Chizat, Maria Colombo, Roberto Colombo +1

We study the quantitative convergence of Wasserstein gradient flows of Kernel Mean Discrepancy (KMD) (also known as Maximum Mean Discrepancy (MMD)) functionals. Our setting covers…