264 citations · 937 across the 33 of their papers we have counts for
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stat.ML2020
Amortized Bayesian model comparison with evidential deep learning
Stefan T. Radev, Marco D'Alessandro, Ulf K. Mertens +3
Comparing competing mathematical models of complex natural processes is a shared goal among many branches of science. The Bayesian probabilistic framework offers a principled way t…
stat.ML2020★ 10 cited
BayesFlow: Learning complex stochastic models with invertible neural networks
Stefan T. Radev, Ulf K. Mertens, Andreas Voss +2
Estimating the parameters of mathematical models is a common problem in almost all branches of science. However, this problem can prove notably difficult when processes and model d…