Archive for experimental design
many folks for manifolds [computational methods for probability distributions on manifolds workshop]
Posted in pictures, Travel, University life with tags bootstrap, experimental design, France, generative model, Gromov-Wasserstein, group picture, IHP, Institut Henri Poincaré, inverse problems, kernel Stein discrepancy descent, manifold, manifold exploration, MCMC, mixture models, Paris, workshop on May 27, 2026 by xi'an
computational methods for probability distributions on manifolds (11-13 May, IHP, Paris)
Posted in Books, pictures, Statistics, Travel, University life with tags bootstrap, experimental design, generative model, Gromov-Wasserstein, IHP, Institut Henri Poincaré, inverse problems, kernel Stein discrepancy descent, manifold, manifold exploration, MCMC, mixture models, Paris, workshop on May 12, 2026 by xi'an
This week, we are running a small workshop on Computational methods for probability distributions on manifolds, whose size was dictated by the corresponding surface of the Institut Henri room allotted to us by the IHP administration. Very exciting theme and very exciting program, which more than make up for the unseasonal weather in Paris.
May 11
Guillaume Pouliot – MCMC on Manifolds in Economics
Alessandro Barp – Kernel and Stein discrepancies between distributions, à la Schwartz
Robin Ryder – Coupling MCMC on manifolds
Chang-Han Rhee – Experimental Design on Manifolds
May 12
Gilles Vilmart – High-order sampling of the invariant distribution of ergodic stochastic dynamics: preconditioning and postprocessing
Paul Breiding – Sampling from or near nonlinear algebraic varieties
Nick Whiteley – Statistical exploration of the Manifold Hypothesis
Judith Rousseau – Denoising diffusion Models under the Manifold Hypothesis : A dimension free convergence rate
Manon Michel – Convergence of non-reversible Markov processes via lifting and Flow Poincaré inequality
Tobias Grafke – Sampling Conditioned Diffusions via Pathspace Projected Monte Carlo
Miranda Holmes-Cerfon – Simulating sticky Brownian motion
Agnès Desolneux – Distances “à la Gromov-Wasserstein” for Gaussian Mixture Models
May 13
Giovanni Samaey – Multilevel interacting particle methods for sampling Bayesian inverse problems
Marylou Gabrié – Revisiting enhanced sampling driven by collective variables using generative models
Chris Walker – A Bayesian Perspective on the Maximum Score Problem
Lulu Kang – Active Learning for Manifold Gaussian Process Regression
ERC postdoc position on scalable experimental design, in Oxford, UK
Posted in Statistics, Travel, University life with tags Bayesian deep learning, Britain, data-driven algorithms, ERC, ERC Starting Grant, European Research Council, experimental design, Horizon Europe, LLM, machine learning, postdoctoral position, scalable MCMC, simulation-based inference, UK, UKRI, uncertainty quantification, University of Oxford on August 8, 2025 by xi'an
mostly MC’nuary [10 Jan 2025]
Posted in Books, Statistics, University life with tags CMAP, experimental design, INRIA, Issy-les-Moulineaux, January, MCMC, Mostly MC, Mostly MCMC seminar, Ocean, Paris, PariSanté campus, PDMP, Porte de Versailles, scalable MCMC, seminar, sequential Monte Carlo on January 6, 2025 by xi'an
Andrew in a comic pastiche on France Inter
Posted in Books, Kids, Statistics with tags Andrew Gelman, comic show, experimental design, France Inter, radio show on June 3, 2024 by xi'an
Andrew Gelman became a punchline in a France Inter comic interlude where the actor mentioned his being unavailable as the reason for her appearance, as well as a few buzzwords related with Andrew’s research. The whole sequence was a bit heavy handed, with a pastiche of experimental design, but I wonder at how the writer came with this connection to Andrew, unless this was an insider job!
