30 citations · 91 across the 16 of their papers we have counts for
3 papers · 1 filter
Approximate Bayesian Computation with Path Signatures
Joel Dyer, Patrick Cannon, Sebastian M Schmon
Simulation models often lack tractable likelihood functions, making likelihood-free inference methods indispensable. Approximate Bayesian computation generates likelihood-free post…
Optimal scaling of random-walk Metropolis algorithms using Bayesian large-sample asymptotics
Sebastian M Schmon, Philippe Gagnon
High-dimensional limit theorems have been shown useful to derive tuning rules for finding the optimal scaling in random-walk Metropolis algorithms. The assumptions under which weak…
Generalized Posteriors in Approximate Bayesian Computation
Sebastian M Schmon, Patrick W Cannon, Jeremias Knoblauch
Complex simulators have become a ubiquitous tool in many scientific disciplines, providing high-fidelity, implicit probabilistic models of natural and social phenomena. Unfortunate…