Sirio Legramanti, Daniele Durante, and Pierre Alquier just arXived a massive paper on the concentration of discrepancy–based ABC posteriors via Rademacher complexity, which includes MMD and Wasserstein distance-based ABC methods. The paper provides sufficient conditions under which a discrepancy within the integral probability semimetrics class guarantees uniform convergence and concentration of the induced ABC posterior, […]
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discrepancy–based ABC posteriors via Rademacher complexity
April 18, 2024step-dads with Bayesian design [One World ABC’minar, 21 March]
March 18, 2024The next One World ABC seminar is taking place (on-line, requiring pre-registration) on Thursday 21 March, 9:00am UK time, with Desi Ivanova (University of Oxford), speaking about Step-DAD: Semi-Amortized Policy-Based Bayesian Experimental Design: We develop a semi-amortized, policy-based, approach to Bayesian experimental design (BED) called Step-wise Deep Adaptive Design (Step-DAD). Like existing, fully amortized, policy-based […]
insufficient Gibbs at One World ABC [25/01]
January 22, 2024The next [on-line] One World Approximate Bayesian Computation (ABC) Seminar will be delivered by Antoine Luciano, currently writing his PhD with Robin Ryder and I. It will take place at 9am, UK/GMT time, on Thursday 25 January, with members of the stats lab here in CEREMADE attending Antoine’s lecture live at the PariSanté campus. Here […]
Asymptotics of ABC when summaries converge at heterogeneous rates
November 21, 2023We just posted a new arXival, jointly with Caroline Lawless, Judith Rousseau, and Robin Ryder. This is a significant component of Caroline’s PhD thesis in Oxford, on which we started working during the first COVID lockdown. In this paper, we extend our results with David Frazier, Gael Martin, both with whom I’ll soon be reunited!, […]
Xi'an's Og 