25 citations · 57 across the 18 of their papers we have counts for
3 papers · 1 filter
Simulation-Based Inference: A Practical Guide
Michael Deistler, Jan Boelts, Peter Steinbach +11
A central challenge in many areas of science and engineering is to identify model parameters that are consistent with prior knowledge and empirical data. Bayesian inference offers…
Identifying multi-compartment Hodgkin-Huxley models with high-density extracellular voltage recordings
Ian Christopher Tanoh, Michael Deistler, Jakob H. Macke +1
Multi-compartment Hodgkin-Huxley models are biophysical models of how electrical signals propagate throughout a neuron, and they form the basis of our knowledge of neural computati…
Multifidelity Simulation-based Inference for Computationally Expensive Simulators
Anastasia N. Krouglova, Hayden R. Johnson, Basile Confavreux +2
Across many domains of science, stochastic models are an essential tool to understand the mechanisms underlying empirically observed data. Models can be of different levels of deta…