49 citations · 99 across the 3 of their papers we have counts for
3 papers · 1 filter
Robust and integrative Bayesian neural networks for likelihood-free parameter inference
Fredrik Wrede, Robin Eriksson, Richard Jiang +4
State-of-the-art neural network-based methods for learning summary statistics have delivered promising results for simulation-based likelihood-free parameter inference. Existing ap…
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation
Mattias Åkesson, Prashant Singh, Fredrik Wrede +1
Approximate Bayesian Computation is widely used in systems biology for inferring parameters in stochastic gene regulatory network models. Its performance hinges critically on the a…
Multi-Statistic Approximate Bayesian Computation with Multi-Armed Bandits
Prashant Singh, Andreas Hellander
Approximate Bayesian computation is an established and popular method for likelihood-free inference with applications in many disciplines. The effectiveness of the method depends c…