6 citations · 7 across the 3 of their papers we have counts for
3 papers
stat.ML2016★ 6 cited
Automatic Variational ABC
Alexander Moreno, Tameem Adel, Edward Meeds +2
Approximate Bayesian Computation (ABC) is a framework for performing likelihood-free posterior inference for simulation models. Stochastic Variational inference (SVI) is an appeali…
stat.ML2015★ 1 cited
Hamiltonian ABC
Edward Meeds, Robert Leenders, Max Welling
Approximate Bayesian computation (ABC) is a powerful and elegant framework for performing inference in simulation-based models. However, due to the difficulty in scaling likelihood…
stat.ML2014
POPE: Post Optimization Posterior Evaluation of Likelihood Free Models
Edward Meeds, Michael Chiang, Mary Lee +3
In many domains, scientists build complex simulators of natural phenomena that encode their hypotheses about the underlying processes. These simulators can be deterministic or stoc…