18 citations · 70 across the 28 of their papers we have counts for
3 papers · 2 filters
Amortized Bayesian Inference for Models of Cognition
Stefan T. Radev, Andreas Voss, Eva Marie Wieschen +1
As models of cognition grow in complexity and number of parameters, Bayesian inference with standard methods can become intractable, especially when the data-generating model is of…
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…
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…