8 citations · 16 across the 7 of their papers we have counts for
3 papers · 1 filter
Statistical applications of contrastive learning
Michael U. Gutmann, Steven Kleinegesse, Benjamin Rhodes
The likelihood function plays a crucial role in statistical inference and experimental design. However, it is computationally intractable for several important classes of statistic…
Bayesian Optimal Experimental Design for Simulator Models of Cognition
Simon Valentin, Steven Kleinegesse, Neil R. Bramley +2
Bayesian optimal experimental design (BOED) is a methodology to identify experiments that are expected to yield informative data. Recent work in cognitive science considered BOED f…
Extending the statistical software package Engine for Likelihood-Free Inference
Vasileios Gkolemis, Michael Gutmann
Bayesian inference is a principled framework for dealing with uncertainty. The practitioner can perform an initial assumption for the physical phenomenon they want to model (prior…