18 citations · 23 across the 3 of their papers we have counts for
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stat.ME2022★ 1 cited
Prediction can be safely used as a proxy for explanation in causally consistent Bayesian generalized linear models
Maximilian Scholz, Paul-Christian Bürkner
Bayesian modeling provides a principled approach to quantifying uncertainty in model parameters and model structure and has seen a surge of applications in recent years. Within the…
stat.ME2022★ 18 cited
Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy
Paul-Christian Bürkner, Maximilian Scholz, Stefan T. Radev
Probabilistic (Bayesian) modeling has experienced a surge of applications in almost all quantitative sciences and industrial areas. This development is driven by a combination of s…