Decision-Making

This talk introduces a novel approach that bridges SBI and Pyro to enable simulation-based hierarchical Bayesian inference, combining SBI’s ability to handle intractable simulators with Pyro’s expressive power for complex hierarchical structures.

Invited presentation at the Bernstein Center for Computational Neuroscience Berlin on using SBI methods for parameter inference in models of neural circuits and behavior.

We propose a new method to perform simulation-based inference for mixed data e.g., with continuous and discrete data types, like they often occur in models of decision-making.