
Metrizing Weak Convergence with Maximum Mean Discrepancies
Theorem 12 of SimonGabriel Schölkopf (JMLR, 2018) seemed to close a...
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Minimum Stein Discrepancy Estimators
When maximum likelihood estimation is infeasible, one often turns to sco...
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Statistical Inference for Generative Models with Maximum Mean Discrepancy
While likelihoodbased inference and its variants provide a statisticall...
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Stein Point Markov Chain Monte Carlo
An important task in machine learning and statistics is the approximatio...
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Irreversible Langevin MCMC on Lie Groups
It is wellknown that irreversible MCMC algorithms converge faster to th...
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Hamiltonian Monte Carlo on Symmetric and Homogeneous Spaces via Symplectic Reduction
The Hamiltonian Monte Carlo method generates samples by introducing a me...
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A RiemannianStein Kernel Method
This paper presents a theoretical analysis of numerical integration base...
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Posterior Integration on a Riemannian Manifold
The geodesic Markov chain Monte Carlo method and its variants enable com...
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Geometry and Dynamics for Markov Chain Monte Carlo
Markov Chain Monte Carlo methods have revolutionised mathematical comput...
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Alessandro Barp
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