2 citations · 4 across the 5 of their papers we have counts for
5 papers
Preconditioned Robust Neural Posterior Estimation for Misspecified Simulators
Ryan P. Kelly, David T. Frazier, David J. Warne +1
Simulation-based inference (SBI) enables parameter estimation for complex stochastic models with intractable likelihoods when model simulation is feasible. Neural posterior estimat…
Simulation-based Bayesian inference under model misspecification
Ryan P. Kelly, David J. Warne, David T. Frazier +3
Simulation-based Bayesian inference (SBI) methods are widely used for parameter estimation in complex models where evaluating the likelihood is challenging but generating simulatio…
The Statistical Accuracy of Neural Posterior and Likelihood Estimation
David T. Frazier, Ryan Kelly, Christopher Drovandi +1
Neural posterior estimation (NPE) and neural likelihood estimation (NLE) are machine learning approaches that provide accurate posterior, and likelihood, approximations in complex…
A Comprehensive Guide to Simulation-based Inference in Computational Biology
Xiaoyu Wang, Ryan P. Kelly, Adrianne L. Jenner +2
Computational models are invaluable in capturing the complexities of real-world biological processes. Yet, the selection of appropriate algorithms for inference tasks, especially w…
Preconditioned Neural Posterior Estimation for Likelihood-free Inference
Xiaoyu Wang, Ryan P. Kelly, David J. Warne +1
Simulation based inference (SBI) methods enable the estimation of posterior distributions when the likelihood function is intractable, but where model simulation is feasible. Popul…