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stat.ML2021
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…
stat.ML2020
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…